Psychological counseling simulation and evaluation method based on dynamic personality AI visitor

Abstract

The invention discloses a psychological counseling simulation and evaluation method based on dynamic personality AI visitors, and belongs to the field of psychological evaluation testing, and the method comprises the steps: building a behavior simulation background knowledge base for simulated visitors according to a plurality of behavior mode description data; establishing a behavior simulation background knowledge base for the simulated visitor according to the plurality of behavior mode description data; and generating second interaction information for the first interaction information according to the first interaction information and the behavior simulation background knowledge base so as to complete the psychological counseling simulation process for the simulated visitor. According to the method, the authenticity and diversity of the psychological counseling simulation process are improved, the subjective deviation of manual evaluation is reduced in the evaluation link, and the objectivity and distinction degree of the test result are enhanced.

Description

Technical Field

[0001] This application belongs to the field of psychological assessment and testing, specifically relating to a psychological counseling simulation method based on dynamic personality AI clients, and an evaluation method, device, storage medium, equipment, and computer program product based on the dynamic personality AI clients' psychological counseling simulation. Background Technology

[0002] In the fields of psychological counseling and assessment testing, researchers and educational institutions often need to train and assess the counseling abilities of counselors or test subjects by simulating the interaction process with clients. Traditional applications include teaching and training psychological counselors, case exercises in psychology courses, and competency assessments of counselors by mental health service organizations. These scenarios generally require a system that can simulate real clients to allow for the practice and testing of the psychological counseling process in a safe and controlled environment.

[0003] In existing technologies, simulated psychological counseling is typically achieved using virtual clients based on fixed scripts or rule-based dialogue systems. These systems generally generate client responses through a pre-set question-and-answer database or limited behavioral patterns. Some systems use keyword matching or simple emotion labels to adjust the client's answers in order to reflect changes in the client's psychological state to some extent.

[0004] However, because the simulated client interactions lack authenticity and diversity, the simulation process cannot truly reflect the complex situations in psychological counseling. Summary of the Invention

[0005] This application aims to provide a method for simulating psychological counseling based on dynamic personality AI clients, as well as an evaluation method, device, storage medium, equipment, and computer program product for simulating psychological counseling based on dynamic personality AI clients, which at least solves the problem of the lack of realism and diversity in the interactive performance of psychological counseling simulation.

[0006] In a first aspect, embodiments of this application disclose a psychological counseling simulation method based on dynamic personality AI clients, including: Establish descriptive data on the behavioral patterns of simulated visitors across multiple descriptive dimensions; A background knowledge base for simulating the behavior of the simulated visitors is established based on multiple behavioral pattern description data. Based on the first interaction information and the behavioral simulation background knowledge base, second interaction information is generated in response to the first interaction information to complete the psychological counseling simulation process for the simulated visitor.

[0007] Secondly, embodiments of this application also disclose an evaluation method based on dynamic personality AI-based client psychological counseling simulation, including: The counseling interaction records between the subject and the psychological counseling model based on dynamic personality AI are collected. The psychological counseling model based on dynamic personality AI is used to generate second interaction information based on the first interaction information provided by the subject and the background knowledge base for the behavior simulation of the simulated client, so as to complete the psychological counseling simulation process for the simulated client. The background knowledge base for the behavior simulation is established based on the behavioral pattern description data of the simulated client in multiple descriptive dimensions. Based on the consultation interaction records, determine the test evaluation data of the subject under multiple assessment dimensions; The evaluation results of the subject's psychological counseling ability were determined based on multiple test and assessment data.

[0008] Thirdly, embodiments of this application also disclose a psychological counseling simulation device based on a dynamic personality AI client, comprising: The behavior definition module is used to create description data of the behavioral patterns of simulated visitors across multiple descriptive dimensions. The knowledge base building module is used to build a background knowledge base for the behavior simulation of the simulated visitor based on multiple behavioral pattern description data. The interactive consultation module is used to generate second interactive information based on the first interactive information and the behavioral simulation background knowledge base, so as to complete the psychological consultation simulation process for the simulated visitor.

[0009] Fourthly, embodiments of this application also disclose an evaluation device based on dynamic personality AI-based client psychological counseling simulation, comprising: The data acquisition module is used to collect counseling interaction records between the subject and the psychological counseling model based on dynamic personality AI. The psychological counseling model based on dynamic personality AI is used to generate second interaction information based on the first interaction information provided by the subject and the background knowledge base for behavioral simulation of the simulated client, so as to complete the psychological counseling simulation process for the simulated client. The background knowledge base for behavioral simulation is established based on behavioral pattern description data of the simulated client in multiple descriptive dimensions. The assessment module is used to determine the test assessment data of the subject under multiple assessment dimensions based on the consultation interaction records; The evaluation module is used to determine the evaluation results of the subject's psychological counseling ability based on multiple test evaluation data.

[0010] Fifthly, embodiments of this application also disclose a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the first or second aspect.

[0011] In a sixth aspect, embodiments of this application also disclose an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, performs the steps as described in the first or second aspect.

[0012] In a seventh aspect, embodiments of this application also disclose a computer program product, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps described in the first or second aspect.

[0013] In summary, in this embodiment, by establishing behavioral pattern description data of simulated visitors under multiple descriptive dimensions, the behavior exhibited by visitors can be expressed in a structured way. This provides a comprehensive semantic foundation for subsequent knowledge base construction, enhancing the richness and controllability of simulated visitors' performance during the interaction process. Based on this, a behavioral simulation background knowledge base is established according to the behavioral pattern description data of multiple dimensions, allowing data from different dimensions to be associated and integrated in a unified carrier. This not only ensures the consistency of the visitor's identity and semantic coherence in multiple rounds of interaction but also provides a dynamically updated interface for interaction generation, enabling the visitor's psychological characteristics and interaction rules to be adjusted at any time, thereby enhancing the realism and diversity of the simulation. Furthermore, a second interactive information is generated based on the first interactive information and the behavioral simulation background knowledge base, allowing the visitor's response to be dynamically generated in conjunction with the context. This not only improves the coherence and staged realism of the interaction but also reduces the problems of pattern repetition and scene distortion caused by fixed scripts or static rules. Furthermore, this application further collects interaction records between the subject and the psychological counseling model based on dynamic personality AI, enabling the subject's counseling behavior to be fully preserved and used for subsequent analysis. Based on this, the application determines the subject's test evaluation data across multiple assessment dimensions according to the interaction records, allowing for the quantification of various key indicators. Ultimately, this allows for the objective presentation of the subject's comprehensive abilities. Therefore, the method based on the embodiments of this application, through multi-dimensional modeling, knowledge base integration, and causal closed loops generated by dynamic interaction, reduces the adverse effects of single interaction expression, contextual breaks, and missing stages in existing technologies. This not only enhances the realism and diversity of the psychological counseling simulation process but also reduces subjective bias in the evaluation stage, strengthening the objectivity and discriminative power of test results, providing more valuable technical support for the training and assessment of psychological counselors. Attached Figure Description

[0014] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This is a flowchart illustrating the steps of a psychological counseling simulation method based on dynamic personality AI for clients, as provided in an embodiment of this application. Figure 2 This is a flowchart illustrating the steps of another psychological counseling simulation method based on dynamic personality AI clients provided in this application embodiment; Figure 3 This is a flowchart illustrating the steps of an evaluation method based on dynamic personality AI-based client psychological counseling simulation, as provided in an embodiment of this application. Figure 4 This is a flowchart of another evaluation method based on dynamic personality AI client psychological counseling simulation provided in this application embodiment; Figure 5 This is a schematic diagram of the structure of a psychological counseling simulation device based on dynamic personality AI for clients, provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of an evaluation device based on dynamic personality AI-based client psychological counseling simulation provided in an embodiment of this application; Figure 7 This is a block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0015] Exemplary embodiments of the present application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the scope of the present application to those skilled in the art.

[0016] Figure 1 This application provides a method for simulating psychological counseling based on dynamic personality AI clients, which specifically includes the following steps: Step 101: Establish behavioral pattern description data for simulated visitors across multiple descriptive dimensions.

[0017] In some embodiments of this application, to provide multi-dimensional foundational data for the subsequent behavioral simulation background knowledge base, and to enable richer and more realistic client behavior to be displayed during psychological counseling simulations, behavioral pattern description data for simulated clients will be established under multiple descriptive dimensions. This allows the behavioral pattern characteristics of clients to be systematically recorded. Here, "behavioral pattern description data" refers to the definition and expression of client behavioral characteristics under different dimensions through text or structured information, used for subsequent knowledge base retrieval and updates. This will enable the structured expression of simulated client behavior, thereby improving the richness and controllability of the interaction process, and providing a comprehensive semantic foundation for subsequent knowledge base integration and dynamic interaction generation.

[0018] In a specific example, a simulated client needs to be constructed for psychological counseling training. Behavioral pattern description data can be established based on the client's core beliefs and emotional response patterns across the cognitive-affective-behavioral dimensions. Simultaneously, behavioral pattern description data can be established based on the client's historical counseling records and defense mechanism descriptions across the dynamic state dimension. This yields a set of structured data covering multiple dimensions, which can be used in subsequent psychological counseling simulations to make the simulated client's responses more closely resemble real-life scenarios.

[0019] Step 102: Establish a background knowledge base for simulating the behavior of simulated visitors based on multiple behavioral pattern description data.

[0020] In some embodiments of this application, in order to unify and integrate the previously established multi-dimensional behavioral pattern description data to form a knowledge carrier that can be called and updated, a behavioral simulation background knowledge base for simulated visitors will be established based on the multiple behavioral pattern description data. This allows behavioral features under different dimensions to be associated within the same knowledge base. Here, the "behavioral simulation background knowledge base" refers to a collection of structured behavioral pattern description data, used to provide retrieval basis and constraints during the interaction generation process. This ensures the consistency of identity and semantic coherence of the simulated visitor in multiple rounds of interaction and provides a dynamically updated interface for subsequent interaction generation, allowing the visitor's psychological characteristics and interaction rules to adjust as the consultation process evolves, thereby enhancing the realism and diversity of the simulation.

[0021] In a specific example, a multi-dimensional behavioral characteristic analysis of simulated clients has already been established. This data from different dimensions can then be input into a unified knowledge base system, allowing it to be associated and retrieved within the same framework. This results in a behavioral simulation background knowledge base. This knowledge base can automatically retrieve relevant dimensional data based on user-input interaction information during subsequent psychological counseling simulations. This assists language models and other programs in generating responses that conform to context and stage characteristics, thereby making the simulated client's performance more closely resemble real psychological counseling scenarios.

[0022] Step 103: Generate second interaction information based on the first interaction information and the background knowledge base of behavioral simulation to complete the psychological counseling simulation process for the simulated client.

[0023] In some embodiments of this application, to enable the simulated client to respond to user input information in a manner consistent with context and stage characteristics during psychological counseling, thereby completing the interactive loop of the simulated psychological counseling, a second interactive information is generated based on the first interactive information and the behavioral simulation background knowledge base to complete the simulated psychological counseling process for the simulated client. Here, the "second interactive information" refers to the client's response generated by the system, which incorporates multi-dimensional behavioral pattern description data from the background knowledge base. This allows the client's response to be dynamically generated in conjunction with the context, ensuring semantic coherence and identity consistency, thereby enhancing the realism and diversity of the interaction and reducing the problems of pattern repetition and scene distortion caused by fixed scripts or static rules.

[0024] In a specific example, a user inputs initial interaction information during psychological counseling training, such as "The counselor asks the client about their recent emotional state." The system can then call upon the behavioral simulation background knowledge base to generate second interaction information, such as "The client responds that they have felt anxious and experienced insomnia over the past week." This provides the user with a client response that fits the context and stage of the training, allowing the psychological counseling simulation to continue and more closely resemble a real psychological counseling scenario.

[0025] In summary, in this embodiment, by establishing behavioral pattern description data of simulated visitors under multiple descriptive dimensions, the behavior exhibited by visitors can be expressed in a structured way. This provides a comprehensive semantic foundation for subsequent knowledge base construction, enhancing the richness and controllability of simulated visitors' performance during the interaction process. Based on this, a behavioral simulation background knowledge base is established according to the behavioral pattern description data of multiple dimensions, allowing data from different dimensions to be associated and integrated in a unified carrier. This not only ensures the consistency of the visitor's identity and semantic coherence in multiple rounds of interaction but also provides a dynamically updated interface for interaction generation, enabling the visitor's psychological characteristics and interaction rules to be adjusted at any time, thereby enhancing the realism and diversity of the simulation. Furthermore, a second interactive information is generated based on the first interactive information and the behavioral simulation background knowledge base, allowing the visitor's response to be dynamically generated in conjunction with the context. This not only improves the coherence and staged realism of the interaction but also reduces the problems of pattern repetition and scene distortion caused by fixed scripts or static rules. Furthermore, this application further collects interaction records between the subject and the psychological counseling model based on dynamic personality AI, enabling the subject's counseling behavior to be fully preserved and used for subsequent analysis. Based on this, the application determines the subject's test evaluation data across multiple assessment dimensions according to the interaction records, allowing for the quantification of various key indicators. Ultimately, this allows for the objective presentation of the subject's comprehensive abilities. Therefore, the method based on the embodiments of this application, through multi-dimensional modeling, knowledge base integration, and causal closed loops generated by dynamic interaction, reduces the adverse effects of single interaction expression, contextual breaks, and missing stages in existing technologies. This not only enhances the realism and diversity of the psychological counseling simulation process but also reduces subjective bias in the evaluation stage, strengthening the objectivity and discriminative power of test results, providing more valuable technical support for the training and assessment of psychological counselors.

[0026] Figure 2 This application provides another method for simulating psychological counseling based on dynamic personality AI clients, which specifically includes the following steps: Step 201: Establish behavioral pattern description data for simulated visitors across multiple descriptive dimensions.

[0027] The method shown in this step has been explained in step 101 and will not be repeated here.

[0028] Optionally, step 201 includes at least one of the following sub-steps: Sub-step 2011: Based on the identity definition text formed by the simulated visitor's name, age, occupation, educational background, and at least one of the target growth events, establish behavioral pattern description data of the simulated visitor in the profile dimension.

[0029] In some embodiments of this application, it is necessary to define the basic profile characteristics of the simulated client using identity information to maintain the consistency and semantic coherence of the client's identity during the psychological counseling simulation. Specifically, this can be achieved by establishing behavioral pattern description data for the simulated client within the profile dimension based on an identity definition text formed from at least one of the simulated client's name, age, occupation, educational background, and target developmental events. Here, "identity definition text" refers to a structured record of the client's basic identity information and developmental goals, used to invoke and constrain the client's behavior in subsequent interactions. This allows the simulated client to maintain stable identity characteristics during interactions, avoiding identity drift due to context switching, thereby improving the realism and controllability of the psychological counseling simulation.

[0030] In a specific example, the visitor's name can be set as "Li," age 25, occupation as "software engineer," educational background as "bachelor's degree," and goal as "improving workplace communication skills." The system generates an identity definition text based on this information, such as "Li, 25 years old, bachelor's degree software engineer, current goal is to improve workplace communication skills." This results in a profile-based description of behavioral patterns, which can be used in subsequent psychological counseling simulations to ensure the visitor maintains identity consistency throughout the interaction and reflects contextual characteristics related to their profession and growth goals in their responses.

[0031] Sub-step 2012: Based on the behavioral definition text formed by at least one of the simulated visitor's core beliefs, thought process examples, and emotional response patterns, establish behavioral pattern description data of the simulated visitor in the cognitive-emotional-behavioral dimensions.

[0032] In some embodiments of this application, in order to characterize the psychological response patterns of simulated clients through cognitive, emotional, and behavioral features, and to exhibit more realistic interactive performance during the simulated psychological counseling process, behavioral pattern description data of simulated clients in the cognitive-emotional-behavioral dimensions can be established based on behavioral definition text formed by at least one of the simulated client's core beliefs, thought process examples, and emotional response patterns. Here, "behavioral definition text" refers to a structured record of the client's belief system at the cognitive level, reasoning process at the thought level, and response pattern at the emotional level, which is used for subsequent interaction generation. This enables the simulated client's responses to reflect the comprehensive characteristics of cognitive logic, emotional response, and behavioral tendencies, thereby improving the realism and phased coherence of the interaction.

[0033] In a specific example, the client's core belief can be set as "the need to prove their self-worth through work performance," and a thought process example can be provided, such as "when a work task is not completed, the client infers that they are not good enough." Simultaneously, the emotional response pattern can be set as "anxiety and self-blame under stress." Based on this information, the system generates behavioral definition text, such as "the client holds the belief that self-worth depends on work performance at the cognitive level; at the thought level, this manifests as self-denial upon task failure; and at the emotional level, it manifests as anxiety and self-blame." This yields behavioral pattern description data across the cognitive-emotional-behavioral dimensions, which can be used in subsequent psychological counseling simulations to make the client's responses more closely resemble real psychological counseling scenarios.

[0034] Sub-step 2013: Based on the state definition text formed by at least one of the simulated visitor's current psychological characteristics, defense mechanism description, cognitive bias description, and historical counseling records, establish behavioral pattern description data of the simulated visitor in the dynamic state dimension.

[0035] In some embodiments of this application, in order to characterize the psychological state of a simulated client through dynamic psychological features and historical interaction information, and to demonstrate psychological performance that changes with time and context during the psychological counseling simulation, behavioral pattern description data of the simulated client in the dynamic state dimension will be established based on a state definition text formed by at least one of the simulated client's current psychological characteristics, defense mechanism description, cognitive bias description, and historical counseling records. Here, "state definition text" refers to a structured record of the client's psychological state at a specific point in time or in a specific context, including the manifestation of their defense mechanisms, the specific characteristics of their cognitive biases, and the trajectory of psychological changes reflected in historical counseling records. This allows the simulated client's responses to dynamically reflect changes in psychological state, avoiding the uniformity of interaction caused by static settings, thereby improving the realism and phased coherence of the psychological counseling simulation.

[0036] In a specific example, the client's current psychological characteristic can be defined as "long-term anxiety," with a description of defense mechanisms, such as "tendency to avoid topics when facing pressure." Cognitive bias can be described as "overgeneralization, believing one failure represents total failure," combined with historical counseling records, such as "repeatedly exhibiting self-denial tendencies in past counseling sessions." Based on this information, the system generates a state definition text, such as "The client is currently in an anxious state, frequently uses topic avoidance as a defense mechanism, exhibits overgeneralization cognitive bias, and has shown self-denial tendencies in past counseling sessions." This yields a dynamic state-level behavioral pattern description, which can be used in subsequent psychological counseling simulations, allowing the client's responses to reflect dynamic changes in their psychological state, thus more closely resembling real psychological counseling scenarios.

[0037] Sub-step 2014: Based on the defense mechanism definition text formed by the typical topics and / or answer lengths of the simulated visitors at different consultation stages, establish behavioral pattern description data of the simulated visitors under the dimension of interaction rules.

[0038] In some embodiments of this application, in order to characterize the typical topic selection and response characteristics of simulated clients at different counseling stages through interaction rules, and to demonstrate defense mechanisms that conform to the stage-specific characteristics during the psychological counseling simulation, behavioral pattern description data of simulated clients under the dimension of interaction rules will be established based on the defense mechanism definition text formed by the typical topics and / or response lengths corresponding to different counseling stages of the simulated clients. Here, "defense mechanism definition text" refers to recording the interaction characteristics of clients at different stages in a structured manner. For example, in the initial stage, they tend to give short answers or avoid sensitive topics, while in the in-depth stage, they may give longer answers and involve core beliefs. This allows the responses of simulated clients to reflect stage-specific differences and dynamic changes in defense mechanisms, thereby improving the realism and interaction diversity of the psychological counseling simulation.

[0039] In a specific example, we can define the typical topic for a client in the initial stage as "work stress," with a "short response" length. In the exploration stage, the typical topic could be "self-worth," with a "medium-length response," and in the in-depth stage, the typical topic as "childhood experiences," with a "longer response." Based on this information, the system generates defense mechanism definition text, such as, "In the initial stage, the client tends to avoid in-depth discussion with short responses; in the exploration stage, they can provide medium-length responses involving self-worth; and in the in-depth stage, they may offer longer responses touching on childhood experiences." This yields behavioral pattern description data under the interaction rules dimension, which can be used in subsequent psychological counseling simulations to make the client's responses more consistent with the defense mechanism performance at different counseling stages.

[0040] Sub-step 2015: Based on the impedance definition text formed by the impedance triggering conditions and / or impedance manifestation forms corresponding to different levels of counseling impedance performance of simulated visitors, establish behavioral pattern description data of simulated visitors under the impedance rule dimension.

[0041] In some embodiments of this application, in order to characterize the defensive reactions and resistance of simulated clients during psychological counseling through resistance rules, and to exhibit more realistic interaction characteristics at different intensity levels, behavioral pattern description data of simulated clients under the resistance rule dimension will be established based on the resistance definition text formed by the resistance triggering conditions and / or resistance manifestation forms corresponding to different levels of counseling resistance manifestation intensity. Here, "resistance definition text" refers to the structured recording of the triggering conditions (e.g., involving sensitive topics or in-depth exploration questions) and specific manifestation forms (e.g., silence, topic shifting, or emotional response) of clients at different resistance levels. This allows the responses of simulated clients to reflect different degrees of resistance, thereby enhancing the realism and complexity of the psychological counseling simulation and helping subjects better cope with the defensive reactions of clients during training.

[0042] In a specific example, the trigger condition for a client at a low resistance level can be defined as "involving general stressful topics," manifested as "brief answers"; at a medium resistance level, the trigger condition is "involving self-worth or experiences of failure," manifested as "changing the subject or giving ambiguous responses"; and at a high resistance level, the trigger condition is "involving childhood trauma or deep emotions," manifested as "silence or emotional reactions." Based on this information, the system generates resistance definition text, such as "The client exhibits defensiveness with brief answers at low resistance, tends to change the subject at medium resistance, and may exhibit silence or emotional reactions at high resistance." This yields behavioral pattern description data under the resistance rule dimensions, which can be used in subsequent psychological counseling simulations to make the client's responses more consistent with the defense mechanisms exhibited at different resistance levels.

[0043] Step 202: Establish a background knowledge base for simulating the behavior of simulated visitors based on multiple behavioral pattern description data.

[0044] The method shown in this step has been explained in step 102 and will not be repeated here.

[0045] Step 203: Generate third interaction information based on scene description information and behavior simulation background knowledge base, and receive first interaction information corresponding to the third interaction information.

[0046] In some embodiments of this application, in order to introduce scenario-driven interaction during psychological counseling simulation so that the simulated client's response is closer to the actual counseling environment, third interaction information can be generated based on scenario description information and a behavioral simulation background knowledge base, and first interaction information corresponding to the third interaction information can be received, thereby forming a scenario-based interaction loop. Here, "scenario description information" refers to text or structured data used to define the psychological counseling environment, such as counseling stage, topic type, or interaction goal. Combined with multi-dimensional data in the behavioral simulation background knowledge base, it can generate interactive content that conforms to scenario characteristics. This allows the simulated client's response to not only rely on context and background knowledge but also reflect the interaction characteristics of a specific scenario, thereby enhancing the realism and diversity of the simulation process.

[0047] In a specific example, a user needs to undergo psychological counseling training. They can first input a scenario description, such as "Initial counseling stage, topic: work stress." The system then generates a third interactive message based on a behavioral simulation background knowledge base, such as "The client expresses anxiety about work tasks." During training, the user receives this third interactive message and provides corresponding first interactive messages, such as "The counselor inquires about the client's specific sources of stress." This forms a scenario-driven interaction loop, making the simulated client's responses more consistent with the phased characteristics of actual psychological counseling scenarios.

[0048] Step 204: Generate second interaction information based on the first interaction information and the background knowledge base of behavior simulation to complete the psychological counseling simulation process for the simulated client.

[0049] The method shown in this step has been explained in step 103 and will not be repeated here.

[0050] Optionally, the behavioral simulation background knowledge base includes descriptive data to characterize behavioral patterns under the impedance rule dimension. Step 204 includes the following sub-steps: Sub-step 2041: If the first interaction information contains target impedance information corresponding to the target impedance triggering condition, determine the target impedance performance strength level corresponding to the first interaction information, and the impedance performance form under the target impedance performance strength level.

[0051] In some embodiments of this application, in order to identify whether the interactive information input by the subject triggers the client's resistance during a psychological counseling simulation, and thus enable the simulated client to exhibit defensive responses consistent with real counseling scenarios at different resistance levels, the target resistance intensity level corresponding to the first interactive information will be determined if the first interactive information contains target resistance information corresponding to the target resistance triggering condition. Furthermore, the form of resistance at that intensity level will be determined. Here, "target resistance information" refers to the semantic features of the interactive content involving sensitive topics or in-depth exploration questions; "resistance intensity level" refers to the client's defensive response level at different degrees, such as low, medium, and high levels; and "resistance form" refers to specific interactive behaviors, such as brief answers, topic shifting, silence, or emotional responses. This allows the simulated client's responses to dynamically reflect the intensity and form of resistance, thereby enhancing the realism and complexity of the psychological counseling simulation.

[0052] In a specific example, during psychological counseling training, the initial interaction information is input, such as "the counselor asks the client if they are willing to talk about their childhood experiences." The system then recognizes that this interaction information contains target impedance information corresponding to the target impedance trigger condition, namely, "involving topics of childhood trauma." The system then determines the impedance performance intensity level corresponding to this interaction information as "high intensity," and further determines that the impedance performance form at this level is "silence or emotional response." After completing the above execution process, the system obtains a behavioral pattern description result under the impedance rule dimension. This result can be called upon in subsequent interaction generation, making the client's response more consistent with defensive behavior in real psychological counseling scenarios.

[0053] Sub-step 2042: Generate second interaction information corresponding to the first interaction information based on the impedance representation.

[0054] In some embodiments of this application, to enable simulated clients to generate responses corresponding to the subject's input based on identified resistance patterns during simulated psychological counseling, thereby exhibiting defensive reactions consistent with real counseling scenarios, a second interactive message corresponding to the first interactive message can be generated based on the resistance patterns. Here, "resistance patterns" refer to the specific interactive behaviors that clients may adopt at different resistance levels, such as brief answers, topic shifting, silence, or emotional responses. This allows the simulated client's responses to dynamically reflect the specific manifestations of defense mechanisms, thereby enhancing the realism and complexity of the simulated psychological counseling and helping subjects better cope with the client's resistance behavior during training.

[0055] In a specific example, during psychological counseling training, the first interaction information is input, such as "the counselor asks the client if they are willing to talk about their childhood experiences." The system has already determined that the corresponding resistance manifestation for this interaction information is "silence or emotional response." Then, based on this resistance manifestation, the system generates a second interaction information, such as "the client remains silent for a moment, then responds in an emotional tone: 'I don't want to talk about this.'" This results in a second interaction information corresponding to the first, which can be invoked in subsequent psychological counseling simulations to make the client's response more consistent with defensive behaviors in real psychological counseling scenarios.

[0056] Step 205: Generate consultation simulation summary data and / or consultation simulation stage evaluation data for the psychological counseling simulation process, and update the background knowledge base based on the consultation simulation summary data and / or consultation simulation stage evaluation data.

[0057] Among them, the consultation simulation summary data is used to define the semantic coherence and / or identity consistency of simulated clients under the same profile dimension in different psychological counseling simulation processes; the consultation simulation stage evaluation data is used to record the counseling stage in which the psychological counseling simulation process is located.

[0058] In some embodiments of this application, in order to summarize and periodically mark the interaction content during the psychological counseling simulation process to ensure the consistency of the client's identity and semantic coherence, and to reflect the stage evolution of the counseling process, counseling simulation summary data and / or counseling simulation stage evaluation data are generated, and the background knowledge base is updated based on this data. Here, "counseling simulation summary data" refers to text formed by extracting the interaction context, used to define the semantic coherence and identity consistency of the client in different simulation processes within the same profile dimension; "counseling simulation stage evaluation data" refers to records formed by inferring the interaction context, used to mark the stage of the psychological counseling simulation process. This allows the background knowledge base to maintain the stability of the client's identity during the interaction process while dynamically reflecting changes in the counseling stage, thereby improving the realism and diversity of the simulation.

[0059] In a specific example, during psychological counseling training, the system first extracts the interaction context to generate counseling simulation summary data, such as "The client consistently portrays themselves as a young professional throughout the process, maintaining semantically coherent expression." Subsequently, the system infers the interaction context to generate counseling simulation stage evaluation data, such as "The current interaction is in the exploratory stage; the client begins to discuss inner beliefs and emotional reactions." This updating of the background knowledge base preserves the consistency of the client's identity while recording the dynamic evolution of the counseling stages, enabling subsequent interaction generation to more closely resemble real psychological counseling scenarios.

[0060] Optionally, step 205 includes the following sub-steps: Sub-step 2051 involves extracting contextual information from the psychological counseling simulation process to obtain a counseling summary text of the psychological counseling simulation process, and establishing or updating a counseling simulation summary data in the background knowledge base based on the counseling summary text.

[0061] In some embodiments of this application, in order to extract the contextual information in the psychological counseling simulation process in a structured manner to form summary data that reflects the consistency of the client's identity and semantic coherence, the contextual information of the psychological counseling simulation process will be extracted to obtain a counseling summary text of the psychological counseling simulation process. A counseling simulation summary data will then be established or updated in the background knowledge base based on this summary text. Here, "council summary text" refers to text formed by extracting identity information, semantic features, and behavioral patterns during the interaction process. This text is used to maintain the stability of the client's identity and semantic coherence within the same profile dimension. This allows the background knowledge base to dynamically update the client's identity and semantic features, thereby ensuring that the client's responses remain consistent and coherent throughout subsequent interaction generation processes.

[0062] In a specific example, researchers collected interaction records between subjects and simulated clients during psychological counseling training. The system can extract contextual information and generate counseling summary text, such as "The client consistently portrayed themselves as a young professional throughout the process and maintained semantically coherent expression in the interaction." Subsequently, the system builds or updates a counseling simulation summary data in the background knowledge base based on this summary text. This results in a summary data that reflects the client's identity consistency and semantic coherence, which is then used in subsequent psychological counseling simulations to make the client's responses more closely resemble real psychological counseling scenarios.

[0063] Sub-step 2052 involves speculating on the contextual information of the psychological counseling simulation process to obtain stage speculation text of the psychological counseling simulation process, and establishing or updating a counseling stage record data in the background knowledge base based on the stage speculation text.

[0064] In some embodiments of this application, in order to analyze and infer the contextual information of the simulated psychological counseling process to identify the current stage of the counseling and ensure the logical consistency between the simulated client's interactive behavior and the counseling stage, the contextual information of the simulated psychological counseling process is inferred to obtain stage-inferred text of the simulated psychological counseling process. Based on this stage-inferred text, a counseling stage record is established or updated in the background knowledge base. Here, "stage-inferred text" refers to text generated through comprehensive analysis of features such as interactive context, topic depth, response length, and emotional expression, used to identify different stages of the counseling process, such as the initial stage, exploration stage, or in-depth stage. This allows the background knowledge base to dynamically update the counseling stage records, ensuring that the simulated client exhibits behavioral patterns consistent with the stage characteristics in subsequent interactions, thus improving the realism and stage coherence of the psychological counseling simulation.

[0065] In a specific example, researchers collected interaction records between subjects and simulated clients during psychological counseling training. During the execution of the script's steps, the system inferred contextual information, identifying that the interaction content primarily focused on "the client describing work stress and expressing anxiety," with brief responses and avoidance as the emotional manifestation. Based on this, the system generated stage-inferred text, such as "The current counseling is in the initial stage; the client mainly exhibits superficial stress descriptions and avoids in-depth topics." Subsequently, the system established or updated a counseling stage record in the background knowledge base based on this stage-inferred text. This resulted in a record that reflects the characteristics of the counseling stage, which was then used in subsequent psychological counseling simulations to make the client's responses more consistent with the interaction logic of different stages.

[0066] Optionally, in some embodiments of this application, when extracting contextual information in a structured manner during a psychological counseling simulation, the extraction scope can be limited by controlling the context window. For example, the time span of the window, the number of interaction rounds, or a semantic relevance threshold can be set to ensure that the extracted content covers key interaction information while avoiding redundant or irrelevant information. Here, "context window control" refers to constraining the information scope during the extraction process so that the generated counseling summary text remains concise and accurate. This allows the counseling simulation summary data in the background knowledge base to be dynamically updated and remain efficient, thereby providing more accurate contextual support in subsequent interaction generation and avoiding semantic drift or information overload.

[0067] In a specific example, researchers collected interaction records between subjects and simulated clients during psychological counseling training. During the system's execution of the sub-steps, the time span of the context window was set to "the most recent 10 minutes," the number of interaction rounds to "the most recent 5 rounds," and the semantic relevance threshold to "0.8." Based on this, the system performed structured extraction of contextual information, generating counseling summary text, such as "In the most recent 10 minutes of interaction, the client mainly focused on work stress, and their answers centered on anxiety and self-doubt." Subsequently, the system established or updated the counseling simulation summary data in the background knowledge base based on this summary text. Ultimately, this ensured that the obtained summary data was appropriately used in subsequent psychological counseling simulations, making the client's responses more consistent with the contextual logic and maintaining semantic coherence.

[0068] In summary, in this embodiment, by establishing behavioral pattern description data of simulated visitors under multiple descriptive dimensions, the behavior exhibited by visitors can be expressed in a structured way. This provides a comprehensive semantic foundation for subsequent knowledge base construction, enhancing the richness and controllability of simulated visitors' performance during the interaction process. Based on this, a behavioral simulation background knowledge base is established according to the behavioral pattern description data of multiple dimensions, allowing data from different dimensions to be associated and integrated in a unified carrier. This not only ensures the consistency of the visitor's identity and semantic coherence in multiple rounds of interaction but also provides a dynamically updated interface for interaction generation, enabling the visitor's psychological characteristics and interaction rules to be adjusted at any time, thereby enhancing the realism and diversity of the simulation. Furthermore, a second interactive information is generated based on the first interactive information and the behavioral simulation background knowledge base, allowing the visitor's response to be dynamically generated in conjunction with the context. This not only improves the coherence and staged realism of the interaction but also reduces the problems of pattern repetition and scene distortion caused by fixed scripts or static rules. Furthermore, this application further collects interaction records between the subject and the psychological counseling model based on dynamic personality AI, enabling the subject's counseling behavior to be fully preserved and used for subsequent analysis. Based on this, the application determines the subject's test evaluation data across multiple assessment dimensions according to the interaction records, allowing for the quantification of various key indicators. Ultimately, this allows for the objective presentation of the subject's comprehensive abilities. Therefore, the method based on the embodiments of this application, through multi-dimensional modeling, knowledge base integration, and causal closed loops generated by dynamic interaction, reduces the adverse effects of single interaction expression, contextual breaks, and missing stages in existing technologies. This not only enhances the realism and diversity of the psychological counseling simulation process but also reduces subjective bias in the evaluation stage, strengthening the objectivity and discriminative power of test results, providing more valuable technical support for the training and assessment of psychological counselors.

[0069] Figure 3This application provides an evaluation method based on dynamic personality AI-based client psychological counseling simulation, which specifically includes the following steps: Step 301: Collect counseling interaction records between the subject and the psychological counseling model based on dynamic personality AI.

[0070] Among them, the psychological counseling model based on dynamic personality AI clients is used to generate second interactive information based on the first interactive information provided by the subjects and the background knowledge base for the simulated client's behavior, so as to complete the psychological counseling simulation process for the simulated client; the background knowledge base for behavior simulation is established based on the behavioral pattern description data of the simulated client in multiple descriptive dimensions.

[0071] In some embodiments of this application, in order to collect the interactive behavior of the subject during the psychological counseling simulation process and provide complete raw data for subsequent testing and evaluation, counseling interaction records between the subject and a psychological counseling model based on a dynamic personality AI client will be collected. This model is used to generate second interactive information based on the first interactive information provided by the subject and the behavioral simulation background knowledge base to complete the psychological counseling simulation process. Here, "counseling interaction records" refers to the interactive text or voice data formed between the subject and the simulated client, including the subject's questions, responses, and the simulated client's feedback. This allows the subject's counseling behavior to be fully preserved and to correspond with the dynamic responses of the simulated client, thereby providing a reliable data foundation for subsequent assessment dimension analysis and ability evaluation.

[0072] In a specific example, researchers set up a simulated scenario in psychological counseling training. Users, acting as subjects, input the first interactive information, such as "The counselor asks the client if they have been feeling stressed recently." The system can then call upon a behavioral simulation background knowledge base to generate the second interactive information, such as "The client responds that they feel stressed at work." The system then collects both the subject's questions and the client's responses as a counseling interaction record, resulting in a complete interaction data file. This file can be used in subsequent analysis to extract assessment indicators such as the subject's communication skills, relationship-building abilities, and ethical compliance.

[0073] In the embodiments of this application, the psychological counseling model based on dynamic personality AI clients can use natural language processing models as examples, such as recurrent neural networks (RNNs), long short-term memory networks (LSTMs), transformer networks, and pre-trained language models (PLMs). These models can express dynamic personality characteristics in dialogue generation and context understanding tasks. The model can be trained using psychological counseling dialogue datasets, psychology case corpora, emotion-annotated interactive datasets, and training corpora containing counseling stage annotations, enabling the model to learn the client's behavioral patterns and interaction characteristics across different dimensions. It should be noted that the specific training methods and implementation details of the model have been fully disclosed and applied in existing technologies, and will not be repeated here.

[0074] Step 302: Determine the test evaluation data of the subject under multiple assessment dimensions based on the consultation interaction record.

[0075] In some embodiments of this application, in order to quantify and analyze the interactive behavior of subjects during a simulated psychological counseling process, and to generate test evaluation data across multiple assessment dimensions, test evaluation data for subjects across multiple assessment dimensions will be determined based on counseling interaction records. These assessment dimensions may include communication skills, relationship-building ability, emotion recognition ability, and ethical compliance, among others. Here, "test evaluation data" refers to structured results obtained through analysis of interaction records, used to reflect the subject's performance across different dimensions. This allows the subject's psychological counseling ability to be decomposed into multiple quantifiable indicators, thus providing a foundation for subsequent comprehensive ability evaluation.

[0076] In a specific example, interaction records between subjects and simulated clients were collected during psychological counseling training. Natural language processing models, such as a Transformer-based text analysis model, were then used to process these records, extracting the subjects' language clarity in the communication skills dimension, response coherence in the relationship-building dimension, and emotion label matching in the emotion recognition dimension. The system then generated a set of test evaluation data, such as "communication skills score 0.75, relationship-building ability score 0.68, emotion recognition ability score 0.72." This data can be further integrated in subsequent steps to form a comprehensive evaluation of the subjects' psychological counseling abilities.

[0077] Step 303: Determine the evaluation results of the subject's psychological counseling ability based on multiple test assessment data.

[0078] In some embodiments of this application, in order to comprehensively process multiple test and assessment data to form an overall evaluation of the subject's psychological counseling ability, the evaluation result of the subject's psychological counseling ability is determined based on multiple test and assessment data. These test and assessment data cover different dimensions such as communication skills, relationship building ability, emotion recognition ability, and ethical compliance. Here, "psychological counseling ability evaluation result" refers to the overall performance index obtained after comprehensive analysis of data from various dimensions, used to reflect the subject's comprehensive ability level in the psychological counseling process. Ultimately, this makes the subject's ability evaluation result more objective and comprehensive, avoiding biases caused by single dimensions or subjective judgments, thereby providing a more valuable reference basis for training and assessment.

[0079] In a specific example, test evaluation data of the subjects have been obtained during psychological counseling training. For instance, the communication skills score is 0.75, the relationship-building ability score is 0.68, and the emotion recognition ability score is 0.72. The system can then use data analysis models, such as a weighted average-based comprehensive scoring model or a machine learning-based classification model, to integrate this test evaluation data and generate a psychological counseling ability evaluation result. For example, "The comprehensive ability score is 0.71. The subject performed well in communication skills, but needs further improvement in relationship-building ability." Ultimately, an objective evaluation result is obtained, which can be directly used for the training assessment of psychological counselors or the development of ability improvement plans.

[0080] In summary, in this embodiment, by establishing behavioral pattern description data of simulated visitors under multiple descriptive dimensions, the behavior exhibited by visitors can be expressed in a structured way. This provides a comprehensive semantic foundation for subsequent knowledge base construction, enhancing the richness and controllability of simulated visitors' performance during the interaction process. Based on this, a behavioral simulation background knowledge base is established according to the behavioral pattern description data of multiple dimensions, allowing data from different dimensions to be associated and integrated in a unified carrier. This not only ensures the consistency of the visitor's identity and semantic coherence in multiple rounds of interaction but also provides a dynamically updated interface for interaction generation, enabling the visitor's psychological characteristics and interaction rules to be adjusted at any time, thereby enhancing the realism and diversity of the simulation. Furthermore, a second interactive information is generated based on the first interactive information and the behavioral simulation background knowledge base, allowing the visitor's response to be dynamically generated in conjunction with the context. This not only improves the coherence and staged realism of the interaction but also reduces the problems of pattern repetition and scene distortion caused by fixed scripts or static rules. Furthermore, this application further collects interaction records between the subject and the psychological counseling model based on dynamic personality AI, enabling the subject's counseling behavior to be fully preserved and used for subsequent analysis. Based on this, the application determines the subject's test evaluation data across multiple assessment dimensions according to the interaction records, allowing for the quantification of various key indicators. Ultimately, this allows for the objective presentation of the subject's comprehensive abilities. Therefore, the method based on the embodiments of this application, through multi-dimensional modeling, knowledge base integration, and causal closed loops generated by dynamic interaction, reduces the adverse effects of single interaction expression, contextual breaks, and missing stages in existing technologies. This not only enhances the realism and diversity of the psychological counseling simulation process but also reduces subjective bias in the evaluation stage, strengthening the objectivity and discriminative power of test results, providing more valuable technical support for the training and assessment of psychological counselors.

[0081] Figure 4 This application provides another evaluation method based on dynamic personality AI-based client psychological counseling simulation, which specifically includes the following steps: Step 401: Collect counseling interaction records between the subject and the psychological counseling model based on dynamic personality AI.

[0082] Among them, the psychological counseling model based on dynamic personality AI clients is used to generate second interactive information based on the first interactive information provided by the subjects and the background knowledge base for the simulated client's behavior, so as to complete the psychological counseling simulation process for the simulated client; the background knowledge base for behavior simulation is established based on the behavioral pattern description data of the simulated client in multiple descriptive dimensions.

[0083] The method shown in this step has been explained in step 301 and will not be repeated here.

[0084] Step 402: Determine the test evaluation data of the subject under multiple assessment dimensions based on the consultation interaction record.

[0085] The method shown in this step has been explained in step 302 and will not be repeated here.

[0086] Optionally, step 402 includes the following sub-steps: Sub-step 4021 involves analyzing the communication skills of the subjects as represented in the counseling interaction records to determine the subjects' skill test assessment text and skill test assessment values, which serve as the subjects' test assessment data in the counseling technology dimension.

[0087] In some embodiments of this application, in order to quantify and analyze the communication skills of subjects during simulated psychological counseling processes, and to form objective test evaluation data under the dimension of counseling techniques, the communication skills of subjects as represented in the counseling interaction records will be analyzed to determine the subject's skill test evaluation text and skill test evaluation value, which will then be used as the subject's test evaluation data under the dimension of counseling techniques. Here, "communication skills" refers to the clarity of language, openness of questioning, logicality of response, and effectiveness of information transmission demonstrated by the subject during the interaction; "skill test evaluation text" is a qualitative description of the subject's communication performance; and "skill test evaluation value" is a numerical result that quantifies communication skills. This allows the subject's communication skills to be structured and quantified, thereby providing comparable and traceable data for subsequent comprehensive ability evaluation.

[0088] In a specific example, a natural language processing model can be used to analyze the interaction records to identify the subject's performance in communication skills, such as high clarity of language expression and the ability to ask open-ended questions, but some deficiencies in the logical consistency of responses. Based on this, the system generates a skills test assessment text, such as "The subject was able to clearly express their views and ask open-ended questions during the communication process, but needs further improvement in the logical consistency of their responses." Simultaneously, the system calculates a skills test assessment value, such as "Communication skills score: 0.75." In some embodiments, this assessment value can be further mapped to a Likert scale (Likert) to generate standardized scores, thereby ensuring the comparability of results among different subjects.

[0089] Sub-step 4022 involves analyzing the subject's empathic expression ability and / or the coherence of the expression interaction as represented in the counseling interaction record, in order to determine the subject's relationship test assessment text and relationship test assessment value, as test assessment data for the subject in the counseling relationship dimension.

[0090] In some embodiments of this application, in order to quantify the subject's relationship-building ability during a simulated psychological counseling process and to generate objective test evaluation data under the counseling relationship dimension, the subject's empathic expression ability and / or expressive interaction coherence, as represented in the counseling interaction record, will be analyzed to determine the subject's relationship test evaluation text and relationship test evaluation value, which will then be used as the subject's test evaluation data under the counseling relationship dimension. Here, "empathic expression ability" refers to whether the subject can accurately identify and respond to the client's emotions during the interaction; "expressive interaction coherence" refers to whether the subject can maintain semantic logical continuity and natural connection of responses in the dialogue; "relationship test evaluation text" is a qualitative description of the subject's relationship-building performance; and "relationship test evaluation value" is a numerical result quantified for this dimension. This allows the subject's relationship-building ability to be structured and quantified, thereby providing a more comprehensive basis for subsequent comprehensive ability evaluation. In some embodiments, the evaluation value can be further mapped to the Working Alliance Inventory (WAI) or the Therapy Effectiveness Scale (TES) to generate standardized scores, thereby improving the authority and consistency of the evaluation results.

[0091] In a specific example, a natural language processing model can be used to analyze the interaction records. This analysis can identify that while the subject accurately responds to the client's anxiety with empathic expression, there are shortcomings in the coherence of the interaction, such as a lack of logical connection in some responses. Based on this, the system generates a relationship test assessment text, such as, "The subject demonstrated a certain level of empathy during the interaction, but needs further improvement in maintaining interaction coherence." Simultaneously, the system calculates the relationship test assessment value, such as "Relationship dimension score: 0.68." This yields test assessment data in the counseling relationship dimension, which can be used in subsequent comprehensive evaluations of psychological counseling abilities, making the evaluation results more objective and comprehensive.

[0092] Sub-step 4023 involves analyzing at least one of the subject's initiative in protecting privacy, value neutrality, and behavioral ethical compliance as represented in the consultation interaction record, in order to determine the subject's ethical test evaluation text and ethical test evaluation value, which serve as the subject's test evaluation data under the consultation ethics dimension.

[0093] In some embodiments of this application, in order to quantify the ethical compliance of subjects during simulated psychological counseling processes and to form objective test evaluation data under the ethical dimension of counseling, at least one of the subjects' initiative in protecting privacy, value neutrality, and behavioral ethical compliance, as represented in the counseling interaction records, will be analyzed to determine the subjects' ethical test evaluation text and ethical test evaluation value, which will then be used as the subjects' test evaluation data under the ethical dimension of counseling. Here, "initiative in protecting privacy" refers to whether the subjects can actively avoid disclosing the client's sensitive information during the interaction; "value neutrality" refers to whether the subjects can maintain an attitude of non-bias and non-imposition of personal values ​​during the interaction; and "behavioral ethical compliance" refers to whether the subjects follow the professional ethical norms of psychological counseling during the interaction. In this way, the subjects' ethical performance can be structured and quantified, thereby providing a more comprehensive and objective basis for subsequent comprehensive ability evaluation.

[0094] In a specific example, a natural language processing model can be used to analyze the interaction records. This analysis can identify that the subject actively avoids mentioning the client's specific identity information regarding privacy and maintains an unbiased attitude regarding value neutrality. However, there are some shortcomings in ethical compliance, such as using expressions in responses that might guide the client's value judgments. Based on this, the system generates an ethical assessment text, such as, "The subject effectively protected the client's privacy and maintained value neutrality during the interaction, but further improvement is needed in ethical compliance." Simultaneously, the system calculates an ethical assessment value, such as "Ethical dimension score: 0.70." This results in an assessment of the counseling ethics dimension, which can be used in subsequent comprehensive evaluations of psychological counseling abilities, making the evaluation results more objective and comprehensive. In some embodiments, this assessment value can be further mapped to a Likert scale or Session Evaluation Scale (SES) to generate standardized scores, thereby ensuring that the ethical dimension evaluation results are consistent with industry standards.

[0095] Step 403: Determine the evaluation results of the subject's psychological counseling ability based on multiple test assessment data.

[0096] The method shown in this step has been explained in step 303 and will not be repeated here.

[0097] Step 404: Generate a guidance text for improving the psychological counseling ability of the subjects based on the evaluation results of their psychological counseling ability.

[0098] In some embodiments of this application, in order to provide targeted improvement plans for subjects based on their psychological counseling ability evaluation results, so as to improve their psychological counseling ability in subsequent training or practice, a guidance text for improving the subjects' psychological counseling ability will be generated based on the evaluation results. This guidance text may include suggestions for improvement in areas such as communication skills, relationship building ability, emotion recognition ability, and ethical compliance. Here, "improvement plan guidance text" refers to structured text content generated by the system, used to provide subjects with specific directions for improvement and training priorities, ultimately enabling subjects to obtain personalized improvement plans, reducing potential subjective biases in manual assessment, and thus improving the relevance and practicality of the training.

[0099] In a specific example, during psychological counseling training, the subject's counseling ability evaluation results have been obtained. For instance, the overall ability score is 0.71, indicating good communication skills but relatively weak relationship building ability. At this point, data analysis models, such as rule-based text generation models or improvement suggestion generation models based on pre-trained language models (PLM), can be used to generate improvement guidance text. For example, it might suggest that the subject increase the use of open-ended questions in subsequent training to encourage client expression; and simultaneously strengthen attention to non-verbal cues in relationship building to enhance the depth of interaction and trust. This results in an improvement guidance text that can be directly used to develop the subject's training plan, enabling them to gradually improve their abilities in subsequent psychological counseling practice.

[0100] In summary, in this embodiment, by establishing behavioral pattern description data of simulated visitors under multiple descriptive dimensions, the behavior exhibited by visitors can be expressed in a structured way. This provides a comprehensive semantic foundation for subsequent knowledge base construction, enhancing the richness and controllability of simulated visitors' performance during the interaction process. Based on this, a behavioral simulation background knowledge base is established according to the behavioral pattern description data of multiple dimensions, allowing data from different dimensions to be associated and integrated in a unified carrier. This not only ensures the consistency of the visitor's identity and semantic coherence in multiple rounds of interaction but also provides a dynamically updated interface for interaction generation, enabling the visitor's psychological characteristics and interaction rules to be adjusted at any time, thereby enhancing the realism and diversity of the simulation. Furthermore, a second interactive information is generated based on the first interactive information and the behavioral simulation background knowledge base, allowing the visitor's response to be dynamically generated in conjunction with the context. This not only improves the coherence and staged realism of the interaction but also reduces the problems of pattern repetition and scene distortion caused by fixed scripts or static rules. Furthermore, this application further collects interaction records between the subject and the psychological counseling model based on dynamic personality AI, enabling the subject's counseling behavior to be fully preserved and used for subsequent analysis. Based on this, the application determines the subject's test evaluation data across multiple assessment dimensions according to the interaction records, allowing for the quantification of various key indicators. Ultimately, this allows for the objective presentation of the subject's comprehensive abilities. Therefore, the method based on the embodiments of this application, through multi-dimensional modeling, knowledge base integration, and causal closed loops generated by dynamic interaction, reduces the adverse effects of single interaction expression, contextual breaks, and missing stages in existing technologies. This not only enhances the realism and diversity of the psychological counseling simulation process but also reduces subjective bias in the evaluation stage, strengthening the objectivity and discriminative power of test results, providing more valuable technical support for the training and assessment of psychological counselors.

[0101] like Figure 5 As shown in the illustration, this application also discloses a psychological counseling simulation device 50 based on a dynamic personality AI client, comprising: The behavior definition module 501 is used to create behavioral pattern description data for simulated visitors under multiple descriptive dimensions. The knowledge base building module 502 is used to build a background knowledge base for the behavior simulation of simulated visitors based on multiple behavioral pattern description data. The interactive consultation module 503 is used to generate second interactive information based on the first interactive information and the behavioral simulation background knowledge base, so as to complete the psychological consultation simulation process for the simulated client.

[0102] Optionally, the behavior definition module 501 includes at least one of the following sub-modules: The identity submodule is used to build behavioral pattern description data of simulated visitors in the profile dimension based on the identity definition text formed by the simulated visitor's name, age, occupation, educational background, and at least one of the target growth events. The behavior submodule is used to build behavioral pattern description data of simulated visitors in the cognitive-emotional-behavioral dimensions based on the behavior definition text formed by at least one of the simulated visitors’ core beliefs, thought process examples, and emotional response patterns. The State submodule is used to establish behavioral pattern description data of the simulated client in the dynamic state dimension based on the state definition text formed by at least one of the simulated client's current psychological characteristics, defense mechanism description, cognitive bias description, and historical counseling records. The defense submodule is used to establish behavioral pattern description data of simulated visitors under the dimension of interaction rules, based on the defense mechanism definition text formed by the typical topics and / or answer lengths corresponding to the simulated visitors at different consultation stages. The impedance submodule is used to establish behavioral pattern description data of simulated clients under the impedance rule dimension, based on the impedance definition text formed by the impedance triggering conditions and / or impedance performance forms corresponding to different levels of counseling impedance performance intensity of simulated clients.

[0103] Optionally, the psychological counseling simulation device 50 based on dynamic personality AI clients also includes: The scene interaction module is used to generate third interaction information based on scene description information and behavior simulation background knowledge base, and to receive first interaction information corresponding to the third interaction information.

[0104] Optionally, the psychological counseling simulation device 50 based on dynamic personality AI clients also includes: The knowledge base update module is used to generate consultation simulation summary data and / or consultation simulation stage evaluation data for the psychological counseling simulation process, and to update the background knowledge base based on the consultation simulation summary data and / or consultation simulation stage evaluation data; the consultation simulation summary data is used to define the semantic coherence and / or identity consistency of simulated clients under the same profile dimension in different psychological counseling simulation processes; the consultation simulation stage evaluation data is used to record the counseling stage in the psychological counseling simulation process.

[0105] Optionally, the knowledge base update module includes: The summary submodule is used to extract contextual information from the psychological counseling simulation process to obtain a counseling summary text of the psychological counseling simulation process, and to create or update a counseling simulation summary data in the background knowledge base based on the counseling summary text. The Stage Submodule is used to infer contextual information of the psychological counseling simulation process to obtain stage inference text of the psychological counseling simulation process, and to establish or update a counseling stage record data in the background knowledge base based on the stage inference text.

[0106] Optionally, the behavioral simulation background knowledge base contains descriptive data to characterize behavioral patterns under the impedance rule dimension, and the interactive consultation module 503 includes: The impedance confirmation submodule is used to determine the target impedance performance strength level corresponding to the first interaction information and the impedance performance form under the target impedance performance strength level when the first interaction information contains target impedance information corresponding to the target impedance triggering condition. The interaction submodule is used to generate second interaction information corresponding to the first interaction information based on the impedance representation.

[0107] like Figure 6 As shown in the embodiment, this application also discloses an evaluation device 60 based on dynamic personality AI client psychological counseling simulation, including: The data acquisition module 601 is used to collect counseling interaction records between the subject and the psychological counseling model based on the dynamic personality AI client. The psychological counseling model based on the dynamic personality AI client is used to generate second interaction information based on the first interaction information provided by the subject and the background knowledge base for the behavior simulation of the simulated client, so as to complete the psychological counseling simulation process for the simulated client. The behavior simulation background knowledge base is established based on the behavioral pattern description data of the simulated client under multiple descriptive dimensions. Assessment module 602 is used to determine the test assessment data of the subject under multiple assessment dimensions based on the consultation interaction record; Evaluation module 603 is used to determine the evaluation results of the subject's psychological counseling ability based on multiple test assessment data.

[0108] Optionally, evaluation module 602 includes: The skills submodule is used to analyze the communication skills of the subjects as represented in the counseling interaction records in order to determine the subjects' skills test assessment text and skills test assessment values, which can be used as test assessment data for the subjects in the counseling technology dimension. The relationship submodule is used to analyze the subject's empathic expression ability and / or the coherence of the expression interaction as represented in the counseling interaction record, in order to determine the subject's relationship test assessment text and relationship test assessment value, as test assessment data of the subject in the counseling relationship dimension; The ethics submodule is used to analyze at least one of the subjects' initiative in protecting privacy, value neutrality, and behavioral ethical compliance as represented in the counseling interaction records, in order to determine the subjects' ethical test evaluation text and ethical test evaluation value, which can be used as the subjects' test evaluation data in the counseling ethics dimension.

[0109] Optionally, the evaluation device 60 based on dynamic personality AI-based client psychological counseling simulation also includes: The guidance module is used to generate guidance texts for improving the psychological counseling abilities of the subjects based on the evaluation results of their psychological counseling abilities.

[0110] In summary, in this embodiment, by establishing behavioral pattern description data of simulated visitors under multiple descriptive dimensions, the behavior exhibited by visitors can be expressed in a structured way. This provides a comprehensive semantic foundation for subsequent knowledge base construction, enhancing the richness and controllability of simulated visitors' performance during the interaction process. Based on this, a behavioral simulation background knowledge base is established according to the behavioral pattern description data of multiple dimensions, allowing data from different dimensions to be associated and integrated in a unified carrier. This not only ensures the consistency of the visitor's identity and semantic coherence in multiple rounds of interaction but also provides a dynamically updated interface for interaction generation, enabling the visitor's psychological characteristics and interaction rules to be adjusted at any time, thereby enhancing the realism and diversity of the simulation. Furthermore, a second interactive information is generated based on the first interactive information and the behavioral simulation background knowledge base, allowing the visitor's response to be dynamically generated in conjunction with the context. This not only improves the coherence and staged realism of the interaction but also reduces the problems of pattern repetition and scene distortion caused by fixed scripts or static rules. Furthermore, this application further collects interaction records between the subject and the psychological counseling model based on dynamic personality AI, enabling the subject's counseling behavior to be fully preserved and used for subsequent analysis. Based on this, the application determines the subject's test evaluation data across multiple assessment dimensions according to the interaction records, allowing for the quantification of various key indicators. Ultimately, this allows for the objective presentation of the subject's comprehensive abilities. Therefore, the method based on the embodiments of this application, through multi-dimensional modeling, knowledge base integration, and causal closed loops generated by dynamic interaction, reduces the adverse effects of single interaction expression, contextual breaks, and missing stages in existing technologies. This not only enhances the realism and diversity of the psychological counseling simulation process but also reduces subjective bias in the evaluation stage, strengthening the objectivity and discriminative power of test results, providing more valuable technical support for the training and assessment of psychological counselors.

[0111] This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, this computer program implements the various processes of the above-described embodiments of the psychological counseling simulation method or the evaluation method based on the dynamic personality AI client psychological counseling simulation, and achieves the same technical effect. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0112] Figure 7 This is a block diagram of an electronic device 700 provided in an embodiment of this application. For example, the electronic device 700 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc.

[0113] Reference Figure 7 The electronic device 700 may include one or more of the following components: a processing component 702, a memory 704, a power supply component 706, a multimedia component 708, an audio component 710, an input / output (I / O) interface 712, a sensor component 714, and a communication component 716.

[0114] Processing component 702 typically controls the overall operation of electronic device 700, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 702 may include one or more processors 720 to execute instructions to complete all or part of the steps described above for the psychological counseling simulation method based on dynamic personality AI client or the evaluation method based on the psychological counseling simulation of dynamic personality AI client. Furthermore, processing component 702 may include one or more modules to facilitate interaction between processing component 702 and other components. For example, processing component 702 may include a multimedia module to facilitate interaction between multimedia component 708 and processing component 702.

[0115] Memory 704 is used to store various types of data to support the operation of electronic device 700. Examples of this data include instructions for any application or method operating on electronic device 700, contact data, phonebook data, messages, pictures, multimedia, etc. Memory 704 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0116] Power supply component 706 provides power to various components of electronic device 700. Power supply component 706 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 700.

[0117] Multimedia component 708 includes a screen that provides an output interface between electronic device 700 and user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may not only sense the boundaries of touch or swipe actions but also detect the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 708 includes a front-facing camera and / or a rear-facing camera. When electronic device 700 is in an operating mode, such as shooting mode or multimedia mode, the front-facing camera and / or rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0118] Audio component 710 is used to output and / or input audio signals. For example, audio component 710 includes a microphone (MIC) used to receive external audio signals when electronic device 700 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 704 or transmitted via communication component 716. In some embodiments, audio component 710 also includes a speaker for outputting audio signals.

[0119] I / O interface 712 provides an interface between processing component 702 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0120] Sensor assembly 714 includes one or more sensors for providing state assessments of various aspects of electronic device 700. For example, sensor assembly 714 may detect the on / off state of electronic device 700, the relative positioning of components such as the display and keypad of electronic device 700, changes in position of electronic device 700 or a component of electronic device 700, the presence or absence of user contact with electronic device 700, orientation or acceleration / deceleration of electronic device 700, and temperature changes of electronic device 700. Sensor assembly 714 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 714 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 714 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0121] Communication component 716 facilitates wired or wireless communication between electronic device 700 and other devices. Electronic device 700 can access wireless networks based on communication standards, such as WiFi, carrier networks (such as 2G, 3G, 4G, or 7G), or combinations thereof. In one exemplary embodiment, communication component 716 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 716 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0122] In an exemplary embodiment, the electronic device 700 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to implement the psychological counseling simulation method based on dynamic personality AI clients or the evaluation method based on dynamic personality AI client psychological counseling simulation provided in the embodiments of this application.

[0123] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 704 including instructions, which can be executed by a processor 720 of an electronic device 700 to complete the aforementioned psychological counseling simulation method based on dynamic personality AI clients or the evaluation method based on the psychological counseling simulation of dynamic personality AI clients. For example, the non-transitory storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0124] In an exemplary embodiment, the electronic device 700 may also be provided as a server, including a processing component 702, which further includes one or more processors 720, and memory resources represented by a memory 704 for storing instructions executable by the processing component 702, such as application programs. The application programs stored in the memory 704 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 702 is configured to execute instructions to perform the psychological counseling simulation method based on dynamic personality AI clients or the evaluation method based on dynamic personality AI client psychological counseling simulation provided in the embodiments of this application.

[0125] Electronic device 700 may also include a power supply component 706 configured to perform power management of electronic device 700, a wired or wireless network interface 718 configured to connect electronic device 700 to a network, and an input / output (I / O) interface 712. Electronic device 700 may operate on an operating system stored in memory 704, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, or similar.

[0126] This application also provides a computer program product, including a computer program that, when executed by a processor, implements a psychological counseling simulation method based on dynamic personality AI for clients or an evaluation method based on the psychological counseling simulation of dynamic personality AI for clients.

[0127] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0128] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

[0129] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0130] It will be readily apparent to those skilled in the art that any combination of the above embodiments is feasible. Therefore, any combination of the above embodiments is an implementation scheme of this application. However, due to space limitations, this specification will not describe them in detail here.

[0131] The psychological counseling simulation method or evaluation method based on dynamic personality AI client psychological counseling simulation provided herein is not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. Based on the above description, the required structure for constructing a system with the scheme of this application is obvious. Furthermore, this application is not directed to any particular programming language. It should be understood that the content of this application described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best implementation of this application.

[0132] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0133] Similarly, it should be understood that, for the purpose of simplification and aiding understanding of one or more aspects of the application, various features of the application are sometimes grouped together in a single embodiment, figure, or description thereof in the above description of exemplary embodiments of the application. However, this approach of disclosure should not be construed as reflecting an intention that the claimed application requires more features than expressly recited in each claim. Rather, as reflected in the claims, the application aspect comprises fewer features than all of the features of the single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the application.

[0134] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0135] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, in the claims, any one of the claimed embodiments can be used in any combination.

[0136] The various component embodiments of this application can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components in the dynamic personality AI-based client psychological counseling simulation method or the evaluation method based on dynamic personality AI-based client psychological counseling simulation according to the embodiments of this application. This application can also be implemented as a device or apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such an implementation of this application can be stored on a computer-readable medium or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0137] In another embodiment of the present invention, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute the psychological counseling simulation method based on dynamic personality AI client or the evaluation method based on dynamic personality AI client psychological counseling simulation of the embodiments of this application.

[0138] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0139] It should be noted that the above embodiments are illustrative of this application and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. This application can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0140] It should be noted that, for the sake of simplicity, the method embodiments of this application are all described as a series of actions. However, those skilled in the art should understand that the embodiments of this application are not limited to the described order of actions, because according to the embodiments of this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential to the embodiments of this application.

[0141] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for embodiments of systems or devices, since they are basically similar to the method embodiments, the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0142] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A psychological counseling simulation method based on dynamic personality AI clients, characterized in that, include: Establish descriptive data on the behavioral patterns of simulated visitors across multiple descriptive dimensions; A background knowledge base for simulating the behavior of the simulated visitors is established based on multiple behavioral pattern description data. Based on the first interaction information and the behavioral simulation background knowledge base, second interaction information is generated in response to the first interaction information to complete the psychological counseling simulation process for the simulated visitor.

2. The psychological counseling simulation method based on dynamic personality AI clients as described in claim 1, characterized in that, The psychological counseling simulation method based on dynamic personality AI clients also includes: The system generates third interaction information based on the scene description information and the behavior simulation background knowledge base, and receives first interaction information corresponding to the third interaction information.

3. The psychological counseling simulation method based on dynamic personality AI clients as described in claim 1, characterized in that, The psychological counseling simulation method based on dynamic personality AI clients also includes: Generate consultation simulation summary data and / or consultation simulation stage evaluation data for the psychological counseling simulation process, and update the background knowledge base based on the consultation simulation summary data and / or the consultation simulation stage evaluation data; the consultation simulation summary data is used to define the semantic coherence and / or identity consistency of simulated clients under the same profile dimension in different psychological counseling simulation processes; the consultation simulation stage evaluation data is used to record the counseling stage in which the psychological counseling simulation process is located.

4. The psychological counseling simulation method based on dynamic personality AI clients as described in claim 3, characterized in that, The generation of consultation simulation summary data and / or consultation simulation stage evaluation data for the psychological counseling simulation process, and the updating of the background knowledge base based on the consultation simulation summary data and / or the consultation simulation stage evaluation data, includes: Contextual information of the simulated psychological counseling process is extracted to obtain a counseling summary text of the simulated psychological counseling process, and a counseling simulation summary data is established or updated in the background knowledge base based on the counseling summary text. The contextual information of the simulated psychological counseling process is inferred to obtain the stage inference text of the simulated psychological counseling process, and a counseling stage record data is established or updated in the background knowledge base based on the stage inference text.

5. An evaluation method based on dynamic personality AI-driven client psychological counseling simulation, characterized in that, include: Collect counseling interaction records between the subjects and a psychological counseling model based on dynamic personality AI clients; The psychological counseling model based on dynamic personality AI clients is used to generate second interactive information in response to the first interactive information based on the first interactive information provided by the subject and the background knowledge base for simulating the behavior of the simulated client, so as to complete the psychological counseling simulation process for the simulated client. The behavioral simulation background knowledge base is established based on behavioral pattern description data of the simulated visitors across multiple descriptive dimensions. Based on the consultation interaction records, determine the test evaluation data of the subject under multiple assessment dimensions; The evaluation results of the subject's psychological counseling ability are determined based on multiple test and assessment data.

6. The evaluation method for client psychological counseling simulation based on dynamic personality AI as described in claim 5, characterized in that, The evaluation method based on dynamic personality AI-driven client psychological counseling simulation also includes: Based on the evaluation results of the subject's psychological counseling ability, a guidance text for improving the subject's psychological counseling ability is generated.

7. A psychological counseling simulation device based on dynamic personality AI clients, characterized in that, include: The behavior definition module is used to create description data of the behavioral patterns of simulated visitors across multiple descriptive dimensions. The knowledge base building module is used to build a background knowledge base for the simulated visitor's behavior based on multiple behavioral pattern description data. The interactive consultation module is used to generate second interactive information based on the first interactive information and the behavioral simulation background knowledge base, so as to complete the psychological consultation simulation process for the simulated visitor.

8. An evaluation device based on dynamic personality AI-based client psychological counseling simulation, characterized in that, include: The data acquisition module is used to collect counseling interaction records between the subject and the psychological counseling model based on dynamic personality AI clients; The psychological counseling model based on dynamic personality AI clients is used to generate second interactive information in response to the first interactive information based on the first interactive information provided by the subject and the background knowledge base for simulating the behavior of the simulated client, so as to complete the psychological counseling simulation process for the simulated client. The behavioral simulation background knowledge base is established based on behavioral pattern description data of the simulated visitors across multiple descriptive dimensions. The assessment module is used to determine the test assessment data of the subject under multiple assessment dimensions based on the consultation interaction records; The evaluation module is used to determine the evaluation results of the subject's psychological counseling ability based on multiple test evaluation data.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the method as described in any one of claims 1 to 6.

10. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method as described in any one of claims 1 to 6.

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