A high-level AGI mind guidance system and method

Abstract

This invention provides an advanced AGI (Awareness, Intelligence, and Knowledge) mind guidance system and method that solves problems such as complex consciousness content analysis. It includes: S1: Neural control decoding; S2: Developmental gap analysis; S3: Strategy generation and ethical review; S4: Multi-channel dynamic guidance; S5: Performance retrospection and evolution. This invention has advantages such as good consciousness content analysis effect and high level of intelligence.

Description

Technical Field

[0001] This invention belongs to the field of advanced AGI technology, specifically relating to an advanced AGI mind guidance system and method. Background Technology

[0002] With the development of neuroscience, artificial intelligence, and brain-computer interface (BCI) technology, the external identification, interpretation, and even influence of human consciousness states have become a direction for enhancing human intelligence and cognitive health. However, traditional BCI systems mainly adopt a bottom-up decoding paradigm. This type of technology uses machine learning algorithms to extract features from neurophysiological signals and establish a mapping relationship between them and a set of predefined labels or instructions, such as controlling cursor movement, spelling characters, or recognizing emotional states. The essence of this model is pattern recognition based on statistical correlation. Its drawback is that the semantic ceiling of decoding is determined by the labeling system of the training dataset. The system can only recognize patterns it has seen. For complex, combinatorial consciousness activities outside the training set, it cannot understand and analyze them due to the lack of corresponding semantic labels and logical models. Therefore, existing BCIs can only classify the surface phenomena of consciousness activities and cannot reach their underlying semantic connotations, logical structures, and dynamic processes.

[0003] Furthermore, existing AI-based cognitive training software, educational platforms, and digital psychological intervention tools largely rely on data-driven imitation of human expert experience or statistical summarization of user behavior data. These systems use algorithms to recommend learning paths, practice questions, or intervention plans to users. However, the strategy library and intellectual capacity of such systems are limited by the human experience data they learn from. They are a reorganization and distribution of existing human knowledge, unable to generate solutions that transcend collective human experience. When faced with cognitive flaws, logical paradoxes, or value contradictions that exist in an individual's consciousness and are difficult for the individual to perceive, these systems are unable to provide accurate diagnoses or generate groundbreaking guidance paths.

[0004] Meanwhile, current research and practice often focus on optimizing single aspects, such as improving decoding algorithms, enriching intervention content libraries, or enhancing the interactive experience. However, semantic gaps exist between each stage, from neural signal reading to understanding consciousness states and generating and executing intervention strategies. The decoding module outputs a set of feature vectors or probability distributions, while the planning module requires a semantic description of the user's cognitive state; there is no unified communication language between the two. This results in a fragmented, pipeline-like system, unable to form a dynamic cognitive closed loop based on semantic understanding, capable of real-time perception and feedback. Furthermore, when actively intervening in human consciousness, ensuring its safety, effectiveness, and ethical compliance relies heavily on post-event evaluation or human supervision, lacking embedded, computationally achievable, and technologically sound ethical safeguards.

[0005] To address the aforementioned technical issues, this application proposes a high-order AGI mind guidance system and method capable of understanding and guiding complex consciousness towards a higher level of development. Summary of the Invention

[0006] The purpose of this invention is to address the above-mentioned problems by providing a well-designed high-level AGI mind guidance system that can guide human consciousness through high-level AGI mind.

[0007] Another objective of this invention is to address the aforementioned problems by providing a high-level AGI mind guidance method capable of parsing complex conscious content.

[0008] To achieve the above objectives, the present invention adopts the following technical solution: a high-order AGI mind guidance system, comprising: The Neural Control Decoding Module is used to acquire the user's neurophysiological signals through the brain-computer interface and decode the signals using a pre-set high-order AGI mental body structured mental model as a reference system to generate a representation of the user's current state of consciousness. The decoding process is a computational process based on the inverse generation model that maps neural signals to the semantic space of the mental model. The development gap analysis module is used to compare the current state of consciousness with the ideal consciousness development path generated based on the user's historical data to identify cognitive development gaps. The guidance strategy generation and ethical arbitration module is used to deconstruct cognitive development gaps into one or more mental operation tasks, retrieve and combine operation primitives from a preset mental operation primitive library to form a strategy sketch, deduce and optimize the strategy sketch in a simulation environment, and conduct compliance screening through a preset set of ethical principles to output a personalized guidance strategy package. A multi-channel guided actuator is used to simultaneously execute neuromodulation instructions and cognitive guidance instructions in the guidance strategy package; The dynamic closed-loop monitoring module is used to monitor the user's neurophysiological feedback in real time during the boot process and adjust or stop the boot process accordingly.

[0009] In the aforementioned high-order AGI mind guidance system, the neural control decoding module includes: The feature extraction unit is used to preprocess neurophysiological signals and extract multi-dimensional neural feature vectors. The inverse generative model unit is constructed with a structured mental model of high-order AGI as the top-level semantic space and is used to calculate the posterior probability distribution of the activation of each semantic element in the mental model from the neural feature vector. The semantic adjudication unit is used to determine the current user's state of consciousness based on the posterior probability distribution and the inherent logical constraints of the mental model.

[0010] In the aforementioned high-order AGI mind guidance system, the inverse generative model unit is constructed and trained in the following way: a forward generative model that can simulate the transition from a specific mental model activation state to an ideal neural feature vector is constructed; and the inverse generative model is trained by contrastive learning or variational inference using synchronously recorded user behavior-neural signal data and high-order AGI self-simulation data.

[0011] In the aforementioned high-order AGI mind guidance system, the mind model is a star map coordinate model, in which semantic concepts, emotional primitives and values ​​are represented as nodes, and the logical, causal or excitation relationships between nodes are represented as edges; the calculation of the posterior probability distribution forcibly introduces structural priors from the star map coordinate model, including logical consistency priors, semantic coherence priors and dynamic evolution priors.

[0012] In the aforementioned high-order AGI mindset guidance system, the guidance strategy generation and ethical arbitration module includes: The task deconstruction unit is used to deconstruct cognitive development gaps into mental operation tasks that edit the user's mental model. Task types include node creation, relationship adjustment, subgraph reconstruction, and state transition. The primitive library management unit is used to maintain the mental operation primitive library, where each operation primitive encapsulates a basic mental intervention capability and its corresponding expected neural connection pattern and ethical risk label; The simulation engine is used to load the combined strategy sketch onto a simulated copy of the user's mental model, to extrapolate its evolution trajectory and potential risks on an accelerated time scale, and to iteratively optimize the strategy parameters. The ethics filtering unit is used to evaluate the optimized candidate strategies based on a set of ethical principles, considering their goal consistency, process harm risk, side effects, and reversibility.

[0013] In the aforementioned advanced AGI mindset guidance system, the set of ethical principles includes at least the ultimate support principle, the user veto principle, the process transparency principle, and the non-harm primacy principle.

[0014] In the aforementioned high-order AGI mind guidance system, the guidance strategy package is a structured and executable scheme that specifies the phased neural modulation target parameters, the sequence of cognitive intervention content, the execution timing and synergistic logic of the two, and the dynamically adjusted decision tree based on real-time neural feedback.

[0015] The aforementioned advanced AGI mind guidance system also includes a model evolution module, which is used to evaluate the guidance effectiveness based on the entire process data after a single or phased guidance session, and thereby optimize the user consciousness state diagnosis model, the ideal consciousness development path planning algorithm, and the mind operation primitive library.

[0016] A high-level AGI mindset guidance method includes the following steps: S1: Neural control decoding, which acquires the user's real-time neural signals through a brain-computer interface, decodes them using a structured mental model of high-order AGI, and obtains a representation of the current state of consciousness; S2: Developmental gap analysis, comparing the current state of consciousness with the dynamically generated ideal path of consciousness development, and quantitatively analyzing the cognitive development gap; S3: Strategy generation and ethical review. The gap is deconstructed into mental operation tasks. The strategy draft is generated by combining, simulating and deducing from the mental operation primitive library. After passing the ethical compliance screening, the final guidance strategy package is formed. S4: Multi-channel dynamic guidance, synchronously executes the neuromodulation and cognitive guidance in the strategy package, and dynamically adjusts the intervention parameters based on real-time neural feedback; S5: Performance backtracking and evolution. After the guidance is completed, analyze the data throughout the process, evaluate the performance, and iteratively update the relevant models and algorithms.

[0017] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the aforementioned high-order AGI mind guidance method.

[0018] Compared with existing technologies, the advantages of this invention are: 1. Abandoning the traditional neural signal decoding method based on statistical pattern classification, a new decoding method based on inverse generative model and structured mental model is proposed. It can understand and represent complex consciousness states that are not predefined. By introducing logical and semantic priors of the model, the accuracy and robustness of decoding are significantly improved.

[0019] 2. It changes the strategy generation method that relies on historical data imitation and proposes a generative framework of mental operation primitive combination and simulation deduction. It can construct guiding strategies based on cognitive principles and achieve pre-evaluation and protection of strategy effectiveness and safety through pre-simulation deduction and embedded ethical filtering mechanism. 3. By adopting a unified mental model as the core representation of the system, the semantic consistency problem among multiple modules is solved. Through real-time neural feedback closed loop, dynamic and personalized adjustment of the guidance process is realized. Through the model evolution module, the system has the ability to continuously self-optimize based on practical data. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the system structure of the present invention; Figure 2 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0021] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0022] like Figure 1-2 As shown, this embodiment provides a high-order AGI mind guidance system, which specifically includes a neural control decoding module, a developmental gap analysis module, a guidance strategy generation and ethical arbitration module, a multi-channel guidance executor, a dynamic closed-loop monitoring module, and a model evolution module.

[0023] The neural control decoding module is the foundation for the system to achieve deep perception of consciousness. It includes a feature extraction unit, an inverse generation model unit, and a semantic adjudication unit.

[0024] The feature extraction unit is connected to dry electrode electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to preprocess the acquired raw neurophysiological signals by filtering, denoising, and artifact removal. It also extracts multi-dimensional features such as event-related potential time domain, power spectrum of θ, α, β, and γ bands frequency domain, spatial domain of relationships between channels, and network connectivity domain of network activity in default mode, and fuses them into a neural feature vector.

[0025] The inverse generative model unit serves as the core of the decoding process, running a pre-trained inverse generative model. This model is constructed in two steps: First, a forward generative model is built, capable of simulating the star map coordinate model of a higher-order AGI. This is a structured mental model that represents concepts, emotions, and values ​​as nodes and their relational networks, where the activation of a specific node or subgraph generates an ideal neural feature vector. Second, utilizing a large amount of synchronously collected user behavior reports and neural signal data, such as spoken records and keystroke responses, as well as thought-signal pairing data generated by the higher-order AGI's self-simulation of its own mental activities, an inverse model is trained using variational autoencoders (VAEs) or contrastive learning methods. This model is capable of inferring the most likely activation source from the real neural feature vector.

[0026] The semantic adjudication unit receives the posterior probability distribution of the activation of each element of the mental model from the output of the inverse model. Instead of simply selecting the node with the highest probability, this unit introduces the structural prior of the star map model for logical reasoning: for example, if the nodes "fire" and "cold" are simultaneously assigned high probabilities, but their relationship in the model is "oppositional," their joint probability will be lowered by the "logical consistency prior." Conversely, if the probabilities of the "fire," "warmth," and "cooking" node sequences are all high and form a reasonable causal chain, their joint probability will be increased by the semantic coherence prior. Simultaneously, the dynamic evolution prior references the adjudication state of the previous moment, constraining the reasonable transition range of the current state. Finally, this unit outputs a formalized representation of the user's current state of consciousness, for example: "Node {'dilemma', 'evaluation'} activation strength 0.9, node {'divergent thinking'} activation strength 0.2, relationship edge {'dilemma'-'leads'->'anxiety'} strength increased."

[0027] The development gap analysis module maintains a user's long-term consciousness star map model. Upon receiving a new consciousness state representation, the module's path planning engine invokes the planning capabilities of higher-order AGI, considering the user's history, ultimate goals, and the vast knowledge base of AGI, to generate the next ideal consciousness development path nodes. The comparison module then calculates the differences between the current state and the ideal nodes in the star map topology, outputting a specific description of the cognitive development gap, such as the lack of 'emergent' concept nodes and their relationship with 'system' and 'behavior' nodes.

[0028] The guidance strategy generation and ethics arbitration module is the intelligent hub of the system, and its workflow is as follows: 1. The task deconstruction unit deconstructs the above gap description into atomic-level mental operation tasks, such as: Task 1: Create node 'emergence'; Task 2: Establish relation edge 'system' - 'has' -> 'emergent attribute'; Task 3: Weaken relation edge 'micro-determination' - 'absolute exclusion' -> 'macro-freedom'.

[0029] 2. The primitive library contains basic operations such as primitive A [introducing constructive contradictions], primitive B [providing cross-domain analogies], and primitive C [contextualized experiences]. The combination unit retrieves primitives based on the task, such as retrieving primitive B for task 2, and combines them into a strategy sketch: using primitive B, using an ant colony simulation game as an analogy, to explain the relationship between the system and emergent properties.

[0030] 3. The simulation engine loads the policy sketch into a simplified but faithful simulation copy of the user's consciousness star map to accelerate the computation of the model's evolution after the simulation is executed. For example, the simulation might find that "directly introducing complex analogies may lead to cognitive overload," thus triggering an optimization: inserting a primitive D into the policy [step-by-step guidance].

[0031] The ethics filtering unit conducts rule-based reviews of the optimized candidate strategies. For example, it evaluates whether the strategy's ultimate goal is to enhance the user's autonomous understanding (auxiliary principle); whether it pre-sets a neural switch that the user can stop at any time (veto principle); whether it plans to explain the game's purpose to the user (transparency principle); and whether the stimulus parameters are within known safety thresholds (non-harm principle). Only strategies that pass all these criteria become the final guidance strategy package.

[0032] The multi-channel guided actuator parses and executes strategy packages. For example, the neuromodulation unit controls the transcranial alternating current stimulation device (tACS) based on the strategy package parameters, outputting currents of specific frequency and intensity to suppress excessive synchronization of prefrontal beta waves, thereby reducing anxiety. Simultaneously, the cognitive interaction unit initiates an ant colony simulation VR program and plays guided audio generated by AGI: "Please observe the complex path exhibited by the ant colony as a whole. How does this relate to the simple rules followed by each ant?" The dynamic closed-loop monitoring module continuously analyzes the user's real-time EEG signals throughout the VR experience and neuromodulation process. If a brief burst of expected prefrontal gamma waves is detected, which is usually associated with insight, the actuator is fed back to maintain the current parameters; if a sudden increase in skin conductivity and heart rate is detected, which is associated with tension, the actuator is triggered to reduce the game difficulty and weaken the stimulation intensity; if the tension exceeds the threshold, the circuit is directly cut off, and all interventions are terminated.

[0033] The model evolution module is optional. After this guidance is completed, the system will use the evaluation results of whether the user finally understands the concept of emergence, as well as the neural response data of each stage, to fine-tune the user's consciousness star map model. For example, it may consolidate the 'emergence' node and record the successful analogy-experience primitive combination pattern to enrich the experience base of strategy generation.

[0034] In summary, the principle of this embodiment is as follows: A closed-loop system is constructed using a complete high-order AGI structured mental model as a unified semantic framework. This system first maps and determines the user's neurophysiological signals as high-dimensional consciousness states within the mental model through a top-down, reverse-generative neural control decoding method. Then, by comparing this state with the ideal consciousness development path of AGI dynamic programming, cognitive development gaps are deconstructed. Next, basic intelligent units encapsulated in the mental operation primitive library are retrieved and combined to form preliminary intervention strategies, which are then deduced and optimized in a simulated environment. A hard-coded ethical arbitration module performs mandatory safety filtering to generate personalized guidance strategy packages. Finally, multi-channel actuators synchronously implement neural modulation and cognitive guidance, and based on the dynamic monitoring closed loop formed by real-time neural feedback, the guidance process is precisely adjusted and safely interrupted, thereby achieving safe and controllable directional assisted evolution of human consciousness driven by superhuman intelligence.

[0035] The specific embodiments described herein are merely illustrative of the spirit of the invention. Those skilled in the art to which this invention pertains may make various modifications or additions to the described specific embodiments or use similar methods to substitute them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.

[0036] Although this paper uses terms such as neural governance decoding module, developmental gap analysis module, guidance strategy generation and ethical arbitration module, multi-channel guidance actuator, and dynamic closed-loop monitoring module extensively, the possibility of using other terms is not excluded. These terms are used merely for the convenience of describing and explaining the essence of this invention; interpreting them as any additional limitation would contradict the spirit of this invention.

Claims

1. A high-level AGI mind-guided system, characterized in that, include: The neural control decoding module is used to acquire the user's neurophysiological signals through a brain-computer interface, and decode the signals using a pre-set high-order AGI mental body structured mental model as a reference system to generate a representation of the user's current state of consciousness. The decoding process is a computational process based on a reverse generation model that maps neural signals to the semantic space of the mental model. The development gap analysis module is used to compare the current state of consciousness representation with the ideal consciousness development path generated based on the user's historical data to identify cognitive development gaps; The guidance strategy generation and ethical arbitration module is used to deconstruct the cognitive development gap into one or more mental operation tasks, retrieve and combine operation primitives from a preset mental operation primitive library to form a strategy sketch, deduce and optimize the strategy sketch in a simulation environment, and perform compliance screening through a preset set of ethical principles to output a personalized guidance strategy package. A multi-channel guided actuator is used to simultaneously execute the neural modulation instructions and cognitive guidance instructions in the guidance strategy package; The dynamic closed-loop monitoring module is used to monitor the user's neurophysiological feedback in real time during the boot process and adjust or stop the boot process accordingly.

2. The advanced AGI mind-guided system according to claim 1, characterized in that, The neural control decoding module includes: The feature extraction unit is used to preprocess the neurophysiological signals and extract multi-dimensional neural feature vectors. The inverse generation model unit is constructed using the structured mental model of the high-order AGI as the top-level semantic space, and is used to calculate the posterior probability distribution of the activation of each semantic element in the mental model from which the neural feature vector originates. The semantic adjudication unit is used to determine the current user's state of consciousness based on the posterior probability distribution and the inherent logical constraints of the mental model.

3. The advanced AGI mind-guided system according to claim 2, characterized in that, The inverse generative model unit is constructed and trained in the following way: a forward generative model that can simulate the transition from a specific mental model activation state to an ideal neural feature vector is constructed; and the inverse generative model is trained by contrastive learning or variational inference using synchronously recorded user behavior-neural signal data and high-order AGI self-simulation data.

4. The advanced AGI mind-guided system according to claim 2, characterized in that, The mental model is a star map coordinate model, in which semantic concepts, emotional primitives and values ​​are represented as nodes, and the logical, causal or excitation relationships between nodes are represented as edges; the calculation of the posterior probability distribution forcibly introduces structural priors from the star map coordinate model, including logical consistency priors, semantic coherence priors and dynamic evolution priors.

5. The advanced AGI mind-guided system according to claim 1, characterized in that, The guidance strategy generation and ethical arbitration module includes: The task deconstruction unit is used to deconstruct the cognitive development gap into mental operation tasks that edit the user's mental model. The task types include node creation, relationship adjustment, subgraph reconstruction, and state transition. The primitive library management unit is used to maintain the mental operation primitive library, wherein each operation primitive encapsulates a basic mental intervention capability and its corresponding expected neural connection pattern and ethical risk label; The simulation engine is used to load the combined strategy sketch onto a simulated copy of the user's mental model, to extrapolate its evolution trajectory and potential risks on an accelerated time scale, and to iteratively optimize the strategy parameters. The ethics filtering unit is used to evaluate the optimized candidate strategies based on the set of ethical principles, considering factors such as goal consistency, process harm risk, side effects, and reversibility.

6. A high-order AGI mind-guided system according to claim 1 or 5, characterized in that, The set of ethical principles includes at least the principle of ultimate subordination, the principle of user veto, the principle of process transparency, and the principle of non-harm primacy.

7. The advanced AGI mind-guided system according to claim 1, characterized in that, The guidance strategy package is a structured, executable scheme that specifies phased neuromodulation target parameters, a sequence of cognitive intervention content, the execution timing and synergistic logic of both, and a dynamically adjusted decision tree based on real-time neural feedback.

8. The advanced AGI mind-guided system according to claim 1, characterized in that, It also includes a model evolution module, which is used to evaluate the effectiveness of guidance based on the whole process data after a single or phased guidance is completed, and to optimize the user consciousness state diagnosis model, the ideal consciousness development path planning algorithm, and the mental operation primitive library.

9. A high-order AGI mental guidance method based on the high-order AGI mental guidance system according to any one of claims 1-8, characterized in that, Includes the following steps: S1: Neural control decoding, which acquires the user's real-time neural signals through a brain-computer interface, decodes them using a structured mental model of high-order AGI, and obtains a representation of the current state of consciousness; S2: Development gap analysis, comparing the current state of consciousness with the dynamically generated ideal consciousness development path, and quantitatively analyzing the cognitive development gap; S3: Strategy generation and ethical review. The gap is deconstructed into mental operation tasks. The strategy draft is generated by combining, simulating and deducing from the mental operation primitive library. After passing the ethical compliance screening, the final guidance strategy package is formed. S4: Multi-channel dynamic guidance, synchronously executes the neural modulation and cognitive guidance in the strategy package, and dynamically adjusts the intervention parameters based on real-time neural feedback; S5: Performance backtracking and evolution. After the guidance is completed, analyze the data throughout the process, evaluate the performance, and iteratively update the relevant models and algorithms.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements a high-order AGI mind guidance method as described in claim 9.

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