Cross-dimensional interaction system and method based on self-evolving holographic intelligent agent

Abstract

The application discloses a cross-dimensional interaction system and method based on a self-evolving holographic agent. The system comprises a holographic agent generation module, a cross-dimensional conversion engine, a self-evolving decision module and a multi-dimensional interaction interface module. The holographic agent generation module collects physical and virtual space dual-domain state parameters to generate a holographic agent instance with spatial anchoring properties. The cross-dimensional conversion engine builds a dual-domain space-time alignment coordinate system to ensure complete conversion of the agent form and real-time state synchronization. The self-evolving decision module continuously optimizes the agent behavior strategy and automatically completes structure reorganization and strategy updating when the interaction efficiency is not up to standard. The multi-dimensional interaction interface module couples a tactile feedback, a spatial sound field and a light field rendering unit to realize immersive two-way interaction. The application relies on spatial anchoring coding, cross-dimensional synchronous conversion and closed-loop evolution mechanism to effectively improve the cross-dimensional interaction positioning accuracy, adaptive ability and overall perception coherence.

Description

Technical Field

[0001] This invention relates to the field of holographic interaction technology, and in particular to a cross-dimensional interaction system and method based on a self-evolving holographic intelligent agent. Background Technology

[0002] With the rapid development of holographic display technology and distributed sensing technology, the demand for immersive interaction between physical and virtual spaces is increasing. The development level of holographic interaction systems directly affects the positioning accuracy, strategy adaptability, and perceptual coherence of cross-dimensional interaction.

[0003] Currently, holographic interactive systems have significant limitations: First, existing holographic agent instances lack spatial anchoring attributes. The entity state parameters in physical space and the digital state parameters in virtual space are independent of each other, making it impossible to establish a unified spatiotemporal correlation representation. This leads to inaccurate positioning and morphological drift of holographic agents in cross-dimensional spaces. Second, the behavioral strategies of existing holographic agents are preset fixed values. During interaction, they cannot evolve based on historical interaction records, nor can they fine-tune local parameters based on real-time interaction deviations. This results in rigid interaction responses that are difficult to adapt to dynamically changing interaction needs. Third, the multi-sensory channel outputs of existing systems are asynchronously parallel driven. The mechanical signals of the haptic feedback array, the acoustic signals of the spatial sound field modulator, and the optical signals of the light field rendering engine lack a spatiotemporal synchronous coupling mechanism. This causes the three types of physical effects to arrive asynchronously at the target spatial coordinates, disrupting the continuity and realism of the immersive interactive experience.

[0004] Therefore, there is an urgent need for a cross-dimensional interaction system and method that can realize cross-dimensional form fidelity transformation of holographic intelligent agents, continuous self-optimization of interaction strategies, and spatiotemporal synchronous coupling of multiple perception channels, so as to meet the core requirements of accurate positioning, adaptive strategies and coherent perception in cross-dimensional immersive interaction scenarios. Summary of the Invention

[0005] The main objective of this invention is to provide a cross-dimensional interaction system and method based on a self-evolving holographic intelligent agent, aiming to solve the technical problems of the lack of spatial anchoring attributes, fixed and rigid behavioral strategies, and asynchronous output of multiple sensing channels in existing holographic interaction systems.

[0006] To achieve the above objectives, this invention provides a cross-dimensional interaction system based on a self-evolving holographic intelligent agent, comprising a holographic intelligent agent generation module, a cross-dimensional transformation engine, a self-evolving decision-making module, and a multi-dimensional interaction interface module, wherein: The holographic intelligent agent generation module is used to collect dual-domain state parameters of physical space and virtual space to generate holographic intelligent agent instances with spatial anchoring attributes. The cross-dimensional transformation engine is used to receive the holographic intelligent agent instance, establish a spatiotemporal alignment coordinate system of physical and virtual dual domains, and enable the holographic intelligent agent instance to perform form fidelity transformation and state synchronization in different dimensional spaces. The self-evolutionary decision-making module is used to receive the synchronized holographic agent instance, optimize the behavior strategy based on historical interactions, fine-tune the response mode according to real-time deviations, monitor the decay of interaction efficiency, and trigger the overall structural reorganization and strategy regeneration of the holographic agent instance when the interaction efficiency is lower than a preset threshold. The multi-dimensional interactive interface module is used to receive the optimized holographic intelligent agent instance, and to couple the haptic feedback array, spatial sound field modulator and light field rendering engine in a spatiotemporal synchronization to realize immersive two-way interaction between the user and the holographic intelligent agent instance in a multi-dimensional space.

[0007] Optionally, the holographic intelligent agent generation module includes a perception acquisition unit and a feature encoding unit, wherein: The sensing and acquisition unit is used to acquire dual-domain state parameters of physical space and virtual space through a distributed sensing array, and generate a discretized dual-domain state data stream. The feature encoding unit is used to perform dynamic feature extraction and spatial anchoring encoding on the dual-domain state data stream to generate a holographic intelligent agent instance with spatiotemporal correlation attributes.

[0008] Optionally, the feature encoding unit includes a spatiotemporal correlation construction subunit, used for: The dual-domain state data stream is subjected to temporal window partitioning and spatial grid indexing to establish a binding relationship between discrete data points and spatiotemporal coordinates; Based on the binding relationship, the spatiotemporal association attributes of the holographic intelligent agent instance are generated through an adaptive weight allocation algorithm, enabling the holographic intelligent agent instance to have the anchoring capability for synchronous positioning in a dual-domain space.

[0009] Optionally, the cross-dimensional transformation engine includes a coordinate alignment unit and a topology reconstruction unit, wherein: The coordinate alignment unit is used to perform reference point registration and scale normalization between the physical coordinate system and the digital coordinate system in the virtual space, thereby generating a unified spatiotemporal alignment coordinate system. The topology reconstruction unit is used to perform dimensional adaptation transformation on the geometric topology of the holographic intelligent agent instance based on the spatiotemporal alignment coordinate system, so as to realize the morphological fidelity transformation of the holographic intelligent agent instance in different dimensional spaces.

[0010] Optionally, the topology reconstruction unit includes a morphological fidelity operation subunit, used for: Extract the set of geometric feature vectors of the holographic agent instance in the source dimension space; Based on the dimensional scaling ratio of the spatiotemporal alignment coordinate system, nonlinear interpolation and boundary constraint operations are performed on the geometric feature vector set to generate a faithful morphological description in the target dimensional space, so that the transformed holographic intelligent agent instance maintains the same topological connectivity as the source instance.

[0011] Optionally, the self-evolutionary decision-making module includes a dual-loop feedback unit and a lifetime confidence assessment unit, wherein: The dual-loop feedback unit includes an outer loop evolution subunit and an inner loop fine-tuning subunit. The outer loop evolution subunit is used to train the evolution strategy model based on historical interaction records, and the inner loop fine-tuning subunit is used to trigger local parameter adjustments based on real-time interaction deviations. The lifetime confidence assessment unit is used to monitor the decay of the interaction performance of the holographic intelligent agent instance, and outputs a recombination trigger signal when the interaction performance is lower than a preset threshold.

[0012] Optionally, the lifetime confidence assessment unit includes a performance degradation calculation subunit, used for: Collect the response accuracy, interaction latency, and user feedback rating of the holographic intelligent agent instance within a preset time window, and construct a three-dimensional performance index vector. A weighted attenuation operation is performed on the three-dimensional performance index vector to generate an interaction performance evaluation value. When the interaction performance evaluation value is lower than the preset threshold, the recombination trigger signal is output to the dual-loop feedback unit to drive the holographic intelligent agent instance to perform structural recombination and strategy regeneration.

[0013] Optionally, the multi-dimensional interactive interface module includes a channel fusion unit and a synchronization coupling unit, wherein: The channel fusion unit is used to perform channel normalization and priority arbitration on the mechanical signal of the haptic feedback array, the acoustic signal of the spatial sound field modulator, and the optical signal of the light field rendering engine to generate a fused perception command stream. The synchronous coupling unit is used to perform spatiotemporal phase locking on the fused perception command stream, so that the three types of physical effects, namely tactile, sound field and light field, arrive at the target spatial coordinate point simultaneously, forming an immersive two-way interactive field.

[0014] Optionally, the synchronization coupling unit includes a spatiotemporal phase-locked subunit, used for: Based on the transmission delay characteristics of each channel signal in the fused sensing command stream, the required pre-trigger time offset for each channel is calculated; Based on the pre-trigger time offset, phase compensation is performed on the driving timing of the haptic feedback array, spatial sound field modulator, and light field rendering engine to make the time deviation of the three types of physical effects at the target spatial coordinate point less than the preset synchronization tolerance, thereby achieving spatiotemporal synchronous coupling.

[0015] Optionally, a cross-dimensional interaction method based on a self-evolving holographic intelligent agent is characterized by comprising the following steps: S1. Collect dual-domain state parameters of physical space and virtual space through a distributed sensing array to generate a holographic intelligent agent instance with spatial anchoring attributes. S2. Establish a spatiotemporal alignment coordinate system for the physical and virtual dual domains, and perform morphological fidelity transformation and state synchronization on the holographic intelligent agent instance based on the spatiotemporal alignment coordinate system. S3. The holographic agent instance after synchronization continuously optimizes its behavior strategy and response mode during the interaction process. S4. Monitor the interaction performance of the holographic intelligent agent instance. If it is lower than a preset threshold, trigger structural reorganization and strategy regeneration. S5. The haptic feedback array, spatial sound field modulator and light field rendering engine are spatiotemporally coupled to generate a fused perception output. S6. Based on the fusion perception output, realize immersive two-way interaction between the user and the holographic intelligent agent instance in a multi-dimensional space.

[0016] The beneficial effects of this invention are as follows: the spatial anchoring encoding of state parameters in both physical and virtual spaces is achieved through the holographic intelligent agent generation module; the morphological fidelity conversion and state synchronization of holographic intelligent agent instances between physical and virtual domains are achieved through the cross-dimensional transformation engine; the continuous self-optimization of holographic intelligent agent interaction strategies and lifetime confidence-driven structural reorganization are achieved through the self-evolutionary decision module; and the spatiotemporal synchronous coupling of three types of physical effects—touch, sound field, and light field—is achieved through the multi-dimensional interaction interface module, thereby significantly improving the positioning accuracy, strategy adaptability, and perceptual coherence of cross-dimensional immersive interaction. Attached Figure Description

[0017] Figure 1 This is a block diagram of a cross-dimensional interaction system based on a self-evolving holographic intelligent agent, provided in an embodiment of the present invention. Figure 2 A flowchart illustrating a cross-dimensional interaction method based on a self-evolving holographic intelligent agent, as provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention.

[0018] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the following embodiments are for illustrative purposes only and are not intended to limit the invention.

[0020] The main solution of this invention is a cross-dimensional interaction system and method based on a self-evolving holographic intelligent agent. The system generates holographic intelligent agent instances with spatiotemporal correlation attributes by performing spatial anchoring encoding on the dual-domain state parameters of physical and virtual spaces through a holographic intelligent agent generation module. A spatiotemporal alignment coordinate system is established via a cross-dimensional transformation engine to achieve form-fidelity transformation and state synchronization. A self-evolving decision module is introduced to optimize behavior strategies based on historical interactions, fine-tune response modes according to real-time deviations, monitor interaction performance decay, and trigger overall structural reorganization and strategy regeneration of the holographic intelligent agent instance when the interaction performance falls below a preset threshold. Finally, a multi-dimensional interaction interface module spatiotemporally couples the haptic feedback array, spatial sound field modulator, and light field rendering engine to form an immersive bidirectional interactive field.

[0021] Because existing holographic interactive systems lack spatial anchoring attributes for holographic agent instances, resulting in inaccurate cross-dimensional positioning and form drift, and because behavioral strategies are preset fixed values ​​that are difficult to adapt to dynamic interaction needs, and asynchronous output from multiple sensory channels disrupts the continuity of the immersive interactive experience, the cross-dimensional interactive system and method based on self-evolving holographic agents provided by this invention can achieve high-fidelity form synchronization and continuous self-optimization of holographic agents in both physical and virtual domains, provide spatiotemporally consistent multi-channel sensory coupling output, and transform the interaction performance evaluation results into executable structural reorganization and strategy regeneration decisions, thereby meeting the core requirements for accurate positioning, adaptive strategies, and coherent perception in cross-dimensional immersive interactive scenarios.

[0022] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can understand it.

[0023] Reference Figure 1 The cross-dimensional interaction system based on a self-evolving holographic intelligent agent provided in this embodiment of the invention includes: a holographic intelligent agent generation module, a cross-dimensional transformation engine, a self-evolving decision module, and a multi-dimensional interaction interface module.

[0024] Among them, a holographic intelligent agent refers to a digital interactive entity that has spatial anchoring attributes, can perform form-fidelity transformation between physical and virtual spaces, and continuously optimize its own behavioral strategies; cross-dimensional interaction refers to the immersive two-way information exchange process between users and holographic intelligent agents in a multi-dimensional space composed of physical and virtual spaces.

[0025] As a preferred embodiment of the present invention, in order to obtain accurate physical and virtual space support for spatial anchoring encoding and cross-dimensional morphological fidelity conversion in the system, the holographic intelligent agent is specifically defined as a digital instance with spatiotemporal correlation attributes, and preferably meets the anchoring capability requirement of synchronous positioning in dual-domain space.

[0026] Specifically, its spatial anchoring attributes include: entity coordinate binding relationships in physical space and digital coordinate binding relationships in virtual space. In actual deployment, this holographic intelligent agent typically runs in a hardware environment including a distributed sensing array, a spatial sound field modulator, a light field rendering engine, and a haptic feedback array to create an immersive interactive experience. Due to the differences in coordinate scale and dimensional characteristics between physical and virtual spaces, after processing by the cross-dimensional transformation engine, its morphological representation mainly manifests as at least one of the following: a set of geometric feature vectors, a topological connectivity description, and a fidelity morphological description.

[0027] This cross-dimensional interactive system based on a self-evolving holographic intelligent agent is deployed in a cluster of computing devices, including a central processing unit and a graphics processing unit, or in a distributed cloud computing server cluster. The computing device cluster is equipped with a non-volatile memory array for long-term storage of dual-domain state parameters, historical interaction records, evolutionary strategy model parameters, and user feedback rating data. The system achieves data interaction and command invocation between the holographic intelligent agent generation module, the cross-dimensional transformation engine, the self-evolving decision-making module, and the multi-dimensional interaction interface module through the high-speed data bus and memory sharing mechanism within the computing devices.

[0028] The holographic intelligent agent generation module receives dual-domain state parameters from both physical and virtual spaces via a data input interface. These dual-domain state parameters specifically include entity position and posture data in the physical space, and digital position and posture data in the virtual space. The module is equipped with a sensing and acquisition unit that acquires the dual-domain state parameters through a distributed sensor array, generating a discretized dual-domain state data stream. The module also includes a feature encoding unit that performs dynamic feature extraction and spatial anchoring encoding on the dual-domain state data stream, generating a holographic intelligent agent instance with spatiotemporal correlation attributes. After completing the computation, the module transmits the holographic intelligent agent instance to the cross-dimensional transformation engine.

[0029] The cross-dimensional transformation engine is equipped with a coordinate alignment unit and a topology reconstruction unit. The coordinate alignment unit performs reference point registration and scale normalization between the physical coordinate system and the digital coordinate system in the virtual space, generating a unified spatiotemporal aligned coordinate system. The topology reconstruction unit receives the spatiotemporal aligned coordinate system output by the coordinate alignment unit and extracts the set of geometric feature vectors of the holographic agent instance in the source dimension space. Based on the dimensional scaling ratio of the spatiotemporal aligned coordinate system, the topology reconstruction unit performs nonlinear interpolation and boundary constraint operations on the set of geometric feature vectors to generate a faithful morphological description in the target dimension space. The cross-dimensional transformation engine, based on the spatiotemporal aligned coordinate system, achieves morphological fidelity transformation and state synchronization of the holographic agent instance in different dimension spaces, and transmits the synchronized holographic agent instance to the self-evolutionary decision module.

[0030] The self-evolving decision-making module is equipped with a dual-loop feedback unit and a lifetime confidence assessment unit. The dual-loop feedback unit includes an outer-loop evolution subunit and an inner-loop fine-tuning subunit. The outer-loop evolution subunit trains the evolution strategy model based on historical interaction records, while the inner-loop fine-tuning subunit adjusts local parameters based on real-time interaction deviations. The lifetime confidence assessment unit collects the response accuracy, interaction latency, and user feedback scores of the holographic agent instance within a preset time window to construct a three-dimensional performance index vector. The lifetime confidence assessment unit performs a weighted decay operation on the three-dimensional performance index vector to generate an interaction performance evaluation value, and outputs a reorganization trigger signal to the dual-loop feedback unit when the interaction performance evaluation value falls below a preset threshold. After continuous optimization calculations, the self-evolving decision-making module outputs a holographic agent instance with continuous service capabilities and transmits it to the multi-dimensional interaction interface module.

[0031] The multi-dimensional interactive interface module is equipped with a channel fusion unit and a synchronization coupling unit. The channel fusion unit normalizes and prioritizes the mechanical signals from the haptic feedback array, the acoustic signals from the spatial sound modulator, and the optical signals from the light field rendering engine, generating a fused perception command stream. The synchronization coupling unit calculates the required pre-trigger time offset for each channel based on its transmission delay characteristics. Based on this pre-trigger time offset, it performs phase compensation on the driving timing of the haptic feedback array, spatial sound modulator, and light field rendering engine, ensuring that the time deviation of the three physical effects at the target spatial coordinate point is less than a preset synchronization tolerance. The multi-dimensional interactive interface module outputs the final immersive bidirectional interactive field to the terminal device via a display interface, or overwrites it to a non-volatile memory array for subsequent retrieval.

[0032] The holographic intelligent agent generation module uses a spatial anchoring coding method to reconstruct discrete dual-domain state parameters into holographic intelligent agent instances with spatiotemporal correlation attributes.

[0033] The holographic intelligent agent generation module is equipped with a sensing and acquisition unit. This unit acquires dual-domain state parameters and uses a distributed sensing array to collect the entity states in the physical space. Because the motion trajectories of entities in the physical space exhibit non-linear dynamic changes and are accompanied by local attitude abrupt changes, the sensing and acquisition unit specifically selects a distributed sensing array that provides high spatiotemporal resolution and anti-interference properties. During the acquisition process, the sensing and acquisition unit introduces a data frame encapsulation mechanism with timestamps to ensure the data synchronization of each sensing node. The timestamps quantify the temporal correlation of the data by recording the absolute time information of the data acquisition, thereby suppressing data timing errors caused by network transmission delays and ensuring that the generated dual-domain state data stream conforms to the temporal consistency rules of the real physical space and virtual space.

[0034] The sensing and acquisition unit outputs a discretized dual-domain state data stream through data fusion calculation, and its formula is as follows: in, represents the dual-domain state data stream corresponding to the i-th holographic agent instance; M represents the total number of sensor nodes in the distributed sensor array. This indicates that the i-th holographic agent instance is at time j on the sensing node. The collected state parameter values; This represents the k-th sampling time; N represents the total number of sampling points within a single sampling period.

[0035] The holographic agent generation module is also equipped with a feature encoding unit. In the dual-domain state data stream, the state parameters of the physical space and the virtual space have different dimensions and coordinate references; direct splicing will lead to inaccurate spatial positioning. The feature encoding unit receives the dual-domain state data stream output by the sensing and acquisition unit, and performs temporal window partitioning and spatial grid indexing to establish the binding relationship between discrete data points and spatiotemporal coordinates. Through adaptive weight allocation calculation, the feature encoding unit transforms the dual-domain state data stream into a holographic agent instance describing spatiotemporal correlation attributes.

[0036] The formula for generating holographic agent instances using feature encoding units is as follows: in, This represents the i-th holographic agent instance; W represents the total number of time windows; This represents the adaptive weight coefficient of the i-th holographic agent instance within the w-th time window; This represents the w-th timing window for the two-domain state data stream. The executed spatial grid indexing function is used to establish the binding relationship between discrete data points and spatiotemporal coordinates.

[0037] After completing the aforementioned mathematical analysis steps, the holographic intelligent agent generation module generates a holographic intelligent agent instance with spatiotemporal correlation attributes. The holographic intelligent agent generation module then transmits the holographic intelligent agent instance to the cross-dimensional transformation engine via the system's internal high-speed data bus.

[0038] The cross-dimensional transformation engine uses spatiotemporal alignment and topology reconstruction methods to convert holographic intelligent agent instances into synchronous instances that maintain form fidelity in the target dimensional space.

[0039] The cross-dimensional transformation engine is equipped with a coordinate alignment unit. This unit acquires the dual-domain coordinate information from the holographic agent instance and uses a reference point registration method to align the physical coordinate system with the digital coordinate system in the virtual space. Because the coordinate references in the physical and virtual spaces exhibit non-linear scale differences and are accompanied by local coordinate distortion, the coordinate alignment unit specifically selects a reference point registration method that provides global registration and scale normalization properties. During the registration operation, the coordinate alignment unit introduces an iterative nearest-point method with least-squares constraints to estimate the transformation parameters between the coordinate systems. The least-squares constraint quantifies the registration error by calculating the sum of squared distances between corresponding reference points, thereby suppressing registration deviations caused by coordinate acquisition noise and ensuring that the generated spatiotemporally aligned coordinate system conforms to the true geometric correspondence of the dual-domain space.

[0040] The coordinate alignment unit outputs a unified spatiotemporally aligned coordinate system through iterative optimization calculation, and its formula is as follows: in, T represents the optimal coordinate transformation matrix; T represents the coordinate transformation matrix to be solved, which includes rotation, scaling, and translation parameters; P represents the number of reference point pairs. Represents the coordinate vector of the p-th physical space reference point; This represents the coordinate vector of the p-th virtual space reference point; This represents the regularization coefficient, used to balance registration accuracy and transformation smoothness; This represents the roughness penalty term of the transformation matrix, which quantifies the complexity of the transformation by calculating the magnitude of change in the transformation parameters.

[0041] The cross-dimensional transformation engine is also equipped with a topology reconstruction unit. In the spatiotemporally aligned coordinate system, the set of geometric feature vectors of the holographic agent instance needs to be adapted to the scale characteristics of the target dimension space; direct scaling would lead to topological structure breakage. The topology reconstruction unit receives the spatiotemporally aligned coordinate system output by the coordinate alignment unit and extracts the set of geometric feature vectors of the holographic agent instance in the source dimension space. Based on the dimensional scaling ratio of the spatiotemporally aligned coordinate system, the topology reconstruction unit performs nonlinear interpolation and boundary constraint operations on the set of geometric feature vectors to generate a faithful morphological description in the target dimension space.

[0042] The formula for generating a faithful morphological description from the topology reconstruction unit is as follows: in, This represents the faithful form description of the i-th holographic agent instance in the target dimension space; This represents the function for nonlinear interpolation and boundary constraint operations; Let q represent the q-th geometric feature vector of the i-th holographic agent instance in the source dimension space, where q is a positive integer representing the index of the geometric feature vector; Q represents the total number of geometric feature vectors, where Q is a positive integer. Represents the optimal coordinate transformation matrix; This represents the boundary constraint parameter, which controls the degree to which topological connectivity is preserved during the interpolation process.

[0043] After completing the aforementioned mathematical analysis steps, the cross-dimensional transformation engine generates a holographic intelligent agent instance that maintains form fidelity transformation and state synchronization between physical and virtual spaces. The cross-dimensional transformation engine then transmits the synchronized holographic intelligent agent instance to the self-evolving decision module via the system's high-speed data bus.

[0044] The self-evolving decision-making module uses a dual-loop feedback and lifetime confidence assessment method to transform synchronized holographic agent instances into self-evolving entities with continuous optimization capabilities.

[0045] The self-evolving decision-making module is equipped with a dual-loop feedback unit. This unit comprises an outer-loop evolutionary subunit and an inner-loop fine-tuning subunit. The outer-loop evolutionary subunit acquires historical interaction records and uses a method trained on historical data to generate the evolutionary strategy model. Because user behavior during interactions exhibits non-linear dynamic changes and is accompanied by sudden shifts in intent, the outer-loop evolutionary subunit specifically selects a training method capable of capturing long-term dependencies and possessing policy generalization properties. During training operations, the outer-loop evolutionary subunit introduces a target network update method with an experience replay mechanism to stabilize the training process. The experience replay mechanism breaks data correlation by storing historical interaction state transition samples and randomly sampling, thereby suppressing training oscillations caused by high correlation in continuous interaction data and ensuring that the generated evolutionary strategy model conforms to the real dynamic evolution of interactions.

[0046] The outer ring evolutionary subunit outputs the evolutionary policy model through policy gradient calculation, and its formula is as follows: in, This represents the parameters of the evolutionary strategy model after the (t+1)th iteration; This represents the parameters of the evolutionary strategy model after the t-th iteration; This represents the learning rate, used to control the step size for parameter updates; Indicates the network parameters related to the policy. The gradient of the objective function; The parameter is The strategy network; This represents the batch of historical interaction records sampled from the experience replay pool at the t-th iteration, where t is a positive integer representing the number of iterations.

[0047] The inner-loop fine-tuning subunit receives the evolutionary strategy model output by the outer-loop evolutionary subunit and triggers local parameter adjustments based on real-time interaction deviations. Real-time interaction deviations are calculated by comparing the current interaction output with the user's expected response. The inner-loop fine-tuning subunit employs a local update method with an adaptive learning rate to perform parameter fine-tuning, as shown in the following formula: in, This represents the parameters of the strategy model after local fine-tuning; The adaptive learning rate at time t is dynamically adjusted based on the magnitude of the current interaction deviation. This represents the real-time interaction deviation value at time t, calculated from the actual interaction output. Expected interactive output The differences between them are obtained; Indicates the network parameters related to the policy. The gradient of the local loss function.

[0048] The self-evolving decision-making module is also equipped with a lifetime confidence assessment unit. During the continuous optimization process of the dual-loop feedback unit, the interaction performance of the holographic agent instance gradually decays with the increase of interaction frequency; directly continuing the original strategy will lead to a decline in service quality. The lifetime confidence assessment unit collects the response accuracy, interaction latency, and user feedback scores of the holographic agent instance within a preset time window to construct a three-dimensional performance index vector. Based on weighted decay calculation, the lifetime confidence assessment unit generates an interaction performance evaluation value and outputs a reorganization trigger signal when the interaction performance evaluation value falls below a preset threshold.

[0049] The formula for calculating the interaction performance evaluation value of the lifetime confidence assessment unit is as follows: in, This represents the interaction performance evaluation value of the i-th holographic intelligent agent instance; This represents the weight coefficient of the d-th performance dimension, where d=1 corresponds to response accuracy, d=2 corresponds to interaction latency, and d=3 corresponds to user feedback rating. This represents the current acquired value of the i-th holographic agent instance in the d-th performance dimension; This represents the historical maximum value of the d-th performance dimension; This represents the historical minimum value of the d-th performance dimension; This represents the decay coefficient, used to control the rate at which interaction effectiveness decreases with increasing number of interactions; This represents the cumulative number of interactions for the i-th holographic agent instance since the last structural reorganization.

[0050] When the interaction performance evaluation value is lower than the preset threshold, the condition is met. < At that time, the lifetime confidence assessment unit outputs a reorganization trigger signal to the dual-loop feedback unit, driving the holographic agent instance to perform structural reorganization and policy regeneration. The structural reorganization process includes: resetting the local parameters of the dual-loop feedback unit to the initial state, clearing the old samples in the experience replay pool, and reinitializing the input layer weights of the evolutionary policy model based on the current interaction environment.

[0051] After completing the aforementioned mathematical analysis steps, the self-evolving decision module generates a self-evolving holographic intelligent agent instance with continuous service capabilities. The self-evolving decision module then transmits the optimized holographic intelligent agent instance to the multi-dimensional interactive interface module via the system's internal high-speed data bus.

[0052] The multidimensional interactive interface module uses a channel fusion and synchronous coupling method to convert the interactive output of the optimized holographic intelligent agent instance into a spatiotemporally synchronized immersive two-way interactive field.

[0053] The multi-dimensional interactive interface module is equipped with a channel fusion unit. This unit acquires the optimized interactive output of the holographic intelligent agent instance and uses a channel normalization method to uniformly quantize the mechanical signals of the haptic feedback array, the acoustic signals of the spatial sound field modulator, and the optical signals of the light field rendering engine. Since the three types of physical signals have different dimensions, dynamic ranges, and sampling frequencies, the channel fusion unit specifically selects a channel fusion method that provides linear normalization and priority arbitration attributes. During the fusion operation, the channel fusion unit introduces a weighted fusion mechanism with priority weight allocation to determine the output order and intensity ratio of various signals. Priority weight allocation quantifies the relative importance of various signals by analyzing the user's sensitivity to different sensory channels in the current interactive scenario, thereby suppressing sensory channel conflicts caused by a fixed output order and ensuring that the generated fused sensory command stream conforms to the actual user sensory preference patterns.

[0054] The channel fusion unit outputs a fusion-aware command stream through weighted fusion calculation, and its formula is as follows: in, This represents the fusion perception instruction stream corresponding to the i-th holographic agent instance; This represents the priority weight coefficient of the i-th holographic intelligent agent instance on the m-th perception channel. m=1 corresponds to the haptic feedback array, m=2 corresponds to the spatial sound field modulator, and m=3 corresponds to the light field rendering engine. This represents the original output signal value of the i-th holographic agent instance on the m-th sensing channel; This represents the maximum signal value of the m-th sensing channel; This represents the minimum signal value of the m-th sensing channel.

[0055] The multi-dimensional interactive interface module is also equipped with a synchronization coupling unit. In the fused perception command stream, the transmission delays of various perception channel signals from the computing device to the physical effect device vary. Direct output would cause the three types of physical effects to arrive asynchronously at the target spatial coordinates. The synchronization coupling unit calculates the required pre-trigger time offset for each channel based on the transmission delay characteristics of the signals in the fused perception command stream. Based on the pre-trigger time offset, the synchronization coupling unit performs phase compensation on the driving timing of the haptic feedback array, spatial sound field modulator, and light field rendering engine, ensuring that the time deviation of the three types of physical effects at the target spatial coordinates is less than a preset synchronization tolerance.

[0056] The formula for calculating the pre-trigger time offset by the synchronous coupling unit is as follows: in, This represents the pre-trigger time offset of the i-th holographic agent instance on the m-th sensing channel; This represents the signal transmission delay of the m-th sensing channel; This represents the signal processing delay of the m-th sensing channel; This represents the maximum total delay across all sensing channels, i.e. ; This represents the spatial distance between the interactive target corresponding to the i-th holographic intelligent agent instance and the physical effect device of the m-th sensing channel; This represents the propagation speed of the physical effect in the m-th sensing channel.

[0057] The drive timing control formula after phase compensation by the synchronous coupling unit is as follows: in, This represents the actual driving triggering time of the i-th holographic agent instance on the m-th perception channel; It represents the target interaction time of the i-th holographic intelligent agent instance, that is, the time when the three types of physical effects are expected to arrive at the target spatial coordinate point simultaneously.

[0058] The synchronous coupling unit ensures that the time deviation of the three types of physical effects at the target space coordinate point meets the following requirements through phase-compensated drive timing control: in, This represents the moment when the physical effect of the i-th holographic agent instance on the m-th perception channel actually arrives at the target spatial coordinate point; This indicates the preset synchronization tolerance, which is typically between 1 millisecond and 5 milliseconds.

[0059] After completing the aforementioned mathematical analysis steps, the multidimensional interactive interface module generates a spatiotemporally synchronized immersive bidirectional interactive field. The multidimensional interactive interface module then outputs the immersive bidirectional interactive field to the terminal device via a display interface, or overwrites it into a non-volatile memory array for subsequent use.

[0060] Reference Figure 2 Corresponding to the cross-dimensional interaction system based on a self-evolving holographic intelligent agent provided in the embodiments of the present invention, the embodiments of the present invention also provide a cross-dimensional interaction method based on a self-evolving holographic intelligent agent, the method comprising the following steps: S1. Collect dual-domain state parameters of physical space and virtual space through a distributed sensing array, perform temporal window division and spatial grid indexing on the dual-domain state parameters, establish the binding relationship between discrete data points and spatiotemporal coordinates, and generate a holographic intelligent agent instance with spatial anchoring attributes through adaptive weight allocation calculation. S2. The physical coordinate system and the digital coordinate system of the virtual space are registered with reference points and normalized in scale to generate a unified spatiotemporal alignment coordinate system. The geometric feature vector set of the holographic intelligent agent instance in the source dimension space is extracted. Nonlinear interpolation and boundary constraint operations are performed on the geometric feature vector set according to the dimension scaling ratio of the spatiotemporal alignment coordinate system to generate a faithful morphological description in the target dimension space, thereby realizing the morphological faithful transformation and state synchronization of the holographic intelligent agent instance. S3. The evolutionary strategy model is trained based on historical interaction records, and local parameter adjustments are triggered based on real-time interaction deviations to drive the synchronized holographic agent instance to continuously optimize its behavior strategy and response mode during the interaction process. S4. Collect the response accuracy, interaction latency, and user feedback rating of the holographic intelligent agent instance within a preset time window, construct a three-dimensional performance index vector, perform a weighted decay operation on the three-dimensional performance index vector to generate an interaction performance evaluation value, monitor whether the interaction performance evaluation value is lower than a preset threshold, if so, trigger structural reorganization and strategy regeneration, reset local parameters to the initial state and reinitialize the evolutionary strategy model, and return to step S3; if not, proceed to step S5. S5. The mechanical signal of the haptic feedback array, the acoustic signal of the spatial sound field modulator, and the optical signal of the light field rendering engine are normalized and prioritized to generate a fusion perception command stream. The required pre-trigger time offset of each channel is calculated based on the transmission delay characteristics of each channel signal in the fusion perception command stream. The phase compensation of the three types of driving timing is performed based on the pre-trigger time offset to make the time deviation of the three types of physical effects of haptics, sound field and light field at the target spatial coordinate point less than the preset synchronization tolerance, and a spatiotemporally synchronized fusion perception output is generated. S6. Based on the fusion perception output, realize immersive two-way interaction between the user and the holographic intelligent agent instance in a multi-dimensional space.

[0061] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 3 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores dual-domain state parameters, historical interaction records, evolutionary strategy model parameters, and user feedback scoring data. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a cross-dimensional interaction method based on a self-evolving holographic intelligent agent.

[0062] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device to which the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0063] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0064] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0065] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0066] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this invention are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with relevant regulations.

[0067] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided by this invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0068] The databases involved in the various embodiments provided by this invention may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchain. The processors involved in the various embodiments provided by this invention may be, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc.

[0069] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0070] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A cross-dimensional interactive system based on a self-evolving holographic intelligent agent, characterized in that, It includes a holographic intelligent agent generation module, a cross-dimensional transformation engine, a self-evolving decision-making module, and a multi-dimensional interaction interface module, among which: The holographic intelligent agent generation module is used to collect dual-domain state parameters of physical space and virtual space to generate holographic intelligent agent instances with spatial anchoring attributes. The cross-dimensional transformation engine is used to receive the holographic intelligent agent instance, establish a spatiotemporal alignment coordinate system of physical and virtual dual domains, and enable the holographic intelligent agent instance to perform form fidelity transformation and state synchronization in different dimensional spaces. The self-evolutionary decision-making module is used to receive the synchronized holographic agent instance, optimize the behavior strategy based on historical interactions, fine-tune the response mode according to real-time deviations, monitor the decay of interaction efficiency, and trigger the overall structural reorganization and strategy regeneration of the holographic agent instance when the interaction efficiency is lower than a preset threshold. The multi-dimensional interactive interface module is used to receive the optimized holographic intelligent agent instance, and to couple the haptic feedback array, spatial sound field modulator and light field rendering engine in a spatiotemporal synchronization to realize immersive two-way interaction between the user and the holographic intelligent agent instance in a multi-dimensional space.

2. The cross-dimensional interactive system based on a self-evolving holographic intelligent agent according to claim 1, characterized in that, The holographic intelligent agent generation module includes a perception acquisition unit and a feature encoding unit, wherein: The sensing and acquisition unit is used to acquire dual-domain state parameters of physical space and virtual space through a distributed sensing array, and generate a discretized dual-domain state data stream. The feature encoding unit is used to perform dynamic feature extraction and spatial anchoring encoding on the dual-domain state data stream to generate the holographic intelligent agent instance with spatiotemporal correlation attributes.

3. The cross-dimensional interactive system based on a self-evolving holographic intelligent agent according to claim 2, characterized in that, The feature encoding unit includes a spatiotemporal correlation construction subunit, used for: The dual-domain state data stream is subjected to temporal window partitioning and spatial grid indexing to establish a binding relationship between discrete data points and spatiotemporal coordinates; Based on the binding relationship, the spatiotemporal association attributes of the holographic intelligent agent instance are generated through an adaptive weight allocation algorithm, enabling the holographic intelligent agent instance to have the anchoring capability for synchronous positioning in a dual-domain space.

4. The cross-dimensional interactive system based on a self-evolving holographic intelligent agent according to claim 1, characterized in that, The cross-dimensional transformation engine includes a coordinate alignment unit and a topology reconstruction unit, wherein: The coordinate alignment unit is used to perform reference point registration and scale normalization between the physical coordinate system and the digital coordinate system in the virtual space, thereby generating a unified spatiotemporal alignment coordinate system. The topology reconstruction unit is used to perform dimensional adaptation transformation on the geometric topology of the holographic intelligent agent instance based on the spatiotemporal alignment coordinate system, so as to realize the morphological fidelity transformation of the holographic intelligent agent instance in different dimensional spaces.

5. The cross-dimensional interactive system based on a self-evolving holographic intelligent agent according to claim 4, characterized in that, The topology reconstruction unit includes a morphological fidelity operation subunit, used for: Extract the set of geometric feature vectors of the holographic agent instance in the source dimension space; Based on the dimensional scaling ratio of the spatiotemporal alignment coordinate system, nonlinear interpolation and boundary constraint operations are performed on the geometric feature vector set to generate a faithful morphological description in the target dimensional space, so that the transformed holographic agent instance maintains the same topological connectivity as the source instance.

6. The cross-dimensional interactive system based on a self-evolving holographic intelligent agent according to claim 1, characterized in that, The self-evolving decision module includes a dual-loop feedback unit and a lifetime confidence assessment unit, wherein: The dual-loop feedback unit includes an outer loop evolution subunit and an inner loop fine-tuning subunit. The outer loop evolution subunit is used to train the evolution strategy model based on historical interaction records, and the inner loop fine-tuning subunit is used to trigger local parameter adjustments based on real-time interaction deviations. The lifetime confidence assessment unit is used to monitor the decay of the interaction performance of the holographic intelligent agent instance, and outputs a recombination trigger signal when the interaction performance is lower than a preset threshold.

7. The cross-dimensional interactive system based on a self-evolving holographic intelligent agent according to claim 6, characterized in that, The lifetime confidence assessment unit includes a performance degradation calculation subunit, used for: Collect the response accuracy, interaction latency, and user feedback rating of the holographic intelligent agent instance within a preset time window, and construct a three-dimensional performance index vector. A weighted attenuation operation is performed on the three-dimensional performance index vector to generate an interaction performance evaluation value. When the interaction performance evaluation value is lower than the preset threshold, the recombination trigger signal is output to the dual-loop feedback unit to drive the holographic intelligent agent instance to perform structural recombination and strategy regeneration.

8. The cross-dimensional interactive system based on a self-evolving holographic intelligent agent according to claim 1, characterized in that, The multi-dimensional interactive interface module includes a channel fusion unit and a synchronization coupling unit, wherein: The channel fusion unit is used to perform channel normalization and priority arbitration on the mechanical signal of the haptic feedback array, the acoustic signal of the spatial sound field modulator, and the optical signal of the light field rendering engine to generate a fused perception command stream. The synchronous coupling unit is used to perform spatiotemporal phase locking on the fused perception command stream, so that the three types of physical effects, namely tactile, sound field and light field, arrive at the target spatial coordinate point simultaneously, forming an immersive two-way interactive field.

9. The cross-dimensional interactive system based on a self-evolving holographic intelligent agent according to claim 8, characterized in that, The synchronization coupling unit includes a spatiotemporal phase-locked subunit, used for: Based on the transmission delay characteristics of each channel signal in the fused sensing command stream, the required pre-trigger time offset for each channel is calculated; Based on the pre-trigger time offset, phase compensation is performed on the driving timing of the haptic feedback array, spatial sound field modulator, and light field rendering engine to make the time deviation of the three types of physical effects at the target spatial coordinate point less than the preset synchronization tolerance, thereby achieving spatiotemporal synchronous coupling.

10. A cross-dimensional interaction method based on a self-evolving holographic intelligent agent, characterized in that, The system according to any one of claims 1-9 includes the following steps: S1. Collect dual-domain state parameters of physical space and virtual space through a distributed sensing array to generate a holographic intelligent agent instance with spatial anchoring attributes. S2. Establish a spatiotemporal alignment coordinate system for the physical and virtual dual domains, and perform morphological fidelity transformation and state synchronization on the holographic intelligent agent instance based on the spatiotemporal alignment coordinate system. S3. The holographic agent instance after synchronization continuously optimizes its behavior strategy and response mode during the interaction process. S4. Monitor the interaction performance of the holographic intelligent agent instance. If it is lower than a preset threshold, trigger structural reorganization and strategy regeneration. S5. The haptic feedback array, spatial sound field modulator and light field rendering engine are spatiotemporally coupled to generate a fused perception output. S6. Based on the fusion perception output, realize immersive two-way interaction between the user and the holographic intelligent agent instance in a multi-dimensional space.

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