281 results about "Collaborative interaction" patented technology

The invention relates to a cross-modal knowledge reasoning method based on a multi-modal large model. In a cross-modal knowledge reasoning process, an existing model is usually limited by single-modal information extraction and shallow feature fusion, so that deep semantic association among data such as texts, images and videos is difficult to fully capture. In order to solve the problem, the invention provides a model for fusing multi-modal information such as texts, images, videos, documents and the like, and processing of multi-modal data is converted into unified feature extraction, interaction and deep reasoning tasks by fully utilizing a supervision fine tuning strategy, a self-adaptive attention mechanism and a cross-language processing technology. The model adopts a modular design, integrates multi-source data complementary analysis, spatial-temporal feature modeling and emotional semantic analysis, and realizes multi-modal collaborative interaction, dynamic scene understanding, long video key event analysis and man-machine co-emotional response. Through sufficient training, the multi-modal large model shows excellent logical reasoning ability and emotion understanding ability in a complex cognitive task, and a brand new solution is provided for efficient extraction, deep semantic analysis and intelligent response of cross-modal information.

The invention discloses a virtual-real fusion exhibition display interaction system and a multi-mode perception method, and belongs to the technical field of exhibition display interaction. The system collects audience eyeball fixation points, gesture actions and ambient light data through AR / VR equipment, analyzes coordinates of a region of interest through an eyeball fixation point attention mechanism, a gesture space-time encoder and a multi-modal fusion unit, triggers holographic projection explanation and virtual exhibition stand light and shadow dynamic adjustment (including illumination intensity, color, Gaussian blur and the like) based on a threshold value, and performs real-time display on the virtual exhibition stand. And multi-user collaborative interaction is realized through federal learning. According to the method, reinforcement learning is adopted to optimize an event-driven threshold value, and virtual and real visual splitting is eliminated in combination with ambient light adaptive mapping. The problems of low participation degree, insufficient single-mode interaction information and multi-user cooperation of traditional exhibition are solved, interest analysis accuracy is improved through multi-mode fusion, personalized experience is enhanced through dynamic interaction, the method is suitable for multiple scenes such as museums and science and technology museums, and exhibition intellectualization, immersion and group interaction efficiency are effectively improved.

The invention discloses a laboratory automatic process management and multi-source data fusion system based on the Internet of Things, and belongs to the technical field of laboratory management. The system comprises a sensing layer, an analysis layer, an intelligent management layer and an application layer. The sensing layer carries out global data acquisition and real-time analysis; the analysis layer integrates data, mines an association relationship and optimizes task matching; the intelligent management layer performs full-process automatic management and control on a laboratory, and comprises an equipment cooperation module, a dynamic detection module, a dynamic configuration module, a real-time simulation module, a preset trigger module and an intelligent auditing module; and the application layer performs multi-terminal collaborative interaction and intelligent assistant assistance processing. According to the system, intelligent collaboration of laboratory equipment, automatic detection of samples, dynamic optimization of equipment parameters and automatic early warning and processing of abnormal conditions are realized through technical means such as knowledge graph construction, a digital twinborn technology and multi-mode biological recognition, and the laboratory management efficiency and the data processing accuracy are effectively improved.

The invention belongs to the technical field of smart city construction and intelligent construction management, and particularly relates to an intelligent scheduling and cooperation system and method for the whole life cycle of city reconstruction. The system comprises an edge sensing layer, a digital twinning network module, a space-time brain module, a block chain collaborative trust layer and an XR collaborative interaction layer. The system collects multi-source data of a construction site in real time through a 5G edge device, realizes fusion modeling of BIM, GIS and TIN models by using a graph convolutional neural network, and performs multi-target scheduling optimization in combination with meta reinforcement learning and a dynamic graph neural network; and meanwhile, construction task verification and fund payment linkage is realized through a block chain smart contract, and immersive cooperation and visual acceptance are provided in cooperation with an AR / VR platform. According to the method, the problems of model splitting, scheduling response lagging, low data collaboration efficiency, insufficient credibility of the performance process and the like in the urban reconstruction project are solved, and the intelligence, transparency and automation level of the construction process is remarkably improved.

The invention provides a multifunctional inspection device detection system based on a distribution network mobile operation terminal, and relates to the technical field of electric power detection, and the multifunctional inspection device detection system comprises a portable main terminal of a dynamic collaborative architecture, a wearable terminal for augmented reality interaction and a distributed heterogeneous sensing cluster, which form a closed-loop data chain through an electric power dedicated low-delay wireless communication network; the portable main terminal is integrated with a heterogeneous computing unit with adaptive computing power distribution, can perform real-time fusion analysis on multi-dimensional sensing data, and outputs a visual result containing fault location and confidence; the wearable terminal superposes fault information to a real scene in a three-dimensional marking form through a virtual-real fusion positioning technology, and supports eye movement and voice collaborative interaction; multi-module collaborative acquisition of the distributed heterogeneous sensing cluster is combined with a nanosecond timestamp synchronization mechanism, so that the limitation of traditional single parameter detection is broken through, rich and synchronous basic data is provided for subsequent analysis, and the comprehensiveness of routing inspection is greatly improved.

The invention relates to the technical field of informatization management systems, and particularly discloses an AI-aid decision-making product full-life-cycle informatization management system which comprises a full-link data sensing module, a digital main line construction module, an AI decision-making center module, a service execution interface module and a man-machine collaborative interaction module. The method comprises the following steps: collecting multi-source heterogeneous data of each stage of a full life cycle of a product through a full-link data sensing module to form a full-amount data sequence with a space-time stamp; and in combination with a data fusion engine, an association graph construction unit and a twinborn model driving unit of the digital main line construction module, data cleaning, alignment, semantic fusion and cross-stage association are realized, a dynamically updated product digital twinborn model is constructed, real-time mapping of a physical entity and a virtual model is achieved, and the real-time mapping of the physical entity and the virtual model is realized. Unified and complete data support is provided for full-link decision making, and the problems of data fragmentation and prominent collaborative barriers of a traditional system are thoroughly solved.

The invention is suitable for the field of environment monitoring, and provides a sampling information management system for intelligent environment monitoring, which comprises a user authority management and control module for realizing multi-level authority management based on an RBAC (Role Based Access Control) model; the equipment full life cycle management module monitors the equipment state in real time through the Internet of Things and carries out early warning calibration; the standard dynamic adaptation module intelligently associates a standard with a sampling scene, and synchronously authorizes updating; the sampling closed-loop management module supports double-end cooperation, offline operation and block chain evidence storage; the data interaction and analysis module integrates the data and intelligently predicts the data; the auditing and tracing module records whole-process operation and gives an early warning for abnormity; and the multi-terminal collaborative interaction module is adapted to multiple systems. The monitoring efficiency and the data quality are improved, and support is provided for environmental protection decision making.

The invention belongs to the technical field of image processing, and discloses a remote digital image analysis cooperation system. The virtual diagnosis module is used for collecting a continuous pathological section sequence and carrying out space registration to obtain a registration section; the model building module is used for performing three-dimensional voxel reconstruction on the registration slices to obtain a three-dimensional voxel reconstruction model, and performing semantic enhancement to obtain a three-dimensional pathological voxel model; the collaborative interaction module is used for generating virtual avatars of G experts based on the VR technology, labeling the three-dimensional pathological voxel model and obtaining space anchor point labeling data of the experts; the graph driving module is used for constructing a structured semantic tree according to the space anchor point annotation data, detecting annotation conflicts and obtaining an annotation conflict detection result; the conflict resolution module is used for performing conflict resolution on the marking conflict detection result to obtain a consensus suggestion; the collaborative efficiency and conclusion reliability of remote diagnosis are improved, and a systematic solution is provided for precise diagnosis of complex pathological cases.

The invention discloses a digital large-screen interaction method and device based on multi-agent cooperation and a medium, and relates to the technical field of digital large-screen interaction.The method comprises the steps that postures, expressions and voice data of a user are collected in real time, the attention weight is calculated in combination with spatial position information, the emotional state change rate is monitored, and the user experience is improved in combination with personal historical browsing preferences; acquiring a main interaction user, an emotional state feature and an emotional change trend; according to the main interaction user, the emotional state features and the emotional change trend, obtaining an initial confidence coefficient of the suspected interested field through a semantic understanding model; and based on the candidate guide images, identifying a user selection intention through a multi-modal fusion processing mechanism, calculating a selection probability, triggering content activation of the main interaction area and content dynamic generation of the auxiliary information area, synchronizing state information, and starting an immersive collaborative interaction process. Through three-level collaborative service configuration, the beneficial effects of improving large screen content organization efficiency and enhancing immersive interaction experience are achieved.

The invention discloses an intelligent fusion analysis and decision support system and method for multi-source heterogeneous data of a spacecraft. The intelligent fusion analysis and decision support system for the multi-source heterogeneous data of the spacecraft and the intelligent fusion analysis and decision support method for the multi-source heterogeneous data of the spacecraft are included. The system comprises a dynamic adaptation access layer, a unified semantic modeling layer, a space-time semantic fusion engine, a digital twin collaborative decision-making center, a knowledge enhancement decision-making auxiliary subsystem, a cross-department collaborative interaction platform and a side cloud collaborative intelligent processing framework. The method comprises the steps of multi-source heterogeneous information dynamic access and semantic modeling, space-time and semantic deep fusion, digital twin driven decision deduction, knowledge enhanced decision assistance, cross-department collaborative decision and interaction, edge cloud collaborative intelligent processing and the like. According to the method, the safety, reliability and decision-making efficiency of spacecraft tasks can be remarkably improved, and the method is suitable for development, testing and on-orbit task stages of various spacecrafts.

The invention discloses an atmosphere lamp control method, electronic equipment and a program product. The method comprises the following steps: acquiring PCM data of an audio signal in real time in the music playing process of a vehicle; performing frequency domain analysis on the PCM data corresponding to each audio frame, and extracting frequency information and loudness information; the method comprises the following steps: calculating frequency information and loudness information of a preset number of continuous audio frames, and respectively calculating a frequency change rate and a loudness change rate within a preset time; respectively comparing the frequency change rate and the loudness change rate with corresponding change rate thresholds; and if at least one of the frequency change rate and the loudness change rate exceeds the corresponding change rate threshold value, a corresponding light updating instruction is sent to the atmosphere lamp control module. The music rhythm function of the automotive interior atmosphere lamp can be enhanced, and the cooperative interaction ability of music and the atmosphere lamp is improved.

The invention discloses an on-chain and off-chain collaborative interaction system based on a block chain, and the system comprises a data structure module which is used for designing a composite data structure containing metadata, data content, a hash value and a timestamp, and employs a Merkle tree to manage data; the distributed storage and transmission module is used for storing data under the chain by adopting a distributed file system, storing key data on the chain by using a block chain, and designing a secure transmission protocol; by means of the Merkle tree and Hash verification, data integrity can be quickly and accurately verified, tampering can be perceived, a distributed storage and transmission technology and a two-way synchronization strategy can be designed, on-chain and off-chain efficient collaboration is achieved, data processing efficiency and reliability are improved, data security privacy is guaranteed by means of block chain characteristics and encryption, digital signature and other technologies, and the method is suitable for large-scale popularization and application. Distributed storage and a P2P network facilitate node and capability expansion to adapt to data growth, an intelligent contract is introduced, online and offline data collaborative automatic management is achieved, risks are reduced, and efficiency is improved.

The invention discloses a collaborative interaction intelligent regulation and control method for source network load storage resources, and relates to the technical field of resource regulation and control, and the method comprises the following steps: Sa1, obtaining the real-time fluctuation of a power grid load and the power grid flow distribution in a power grid system, and carrying out the prediction of the power flow distribution based on the real-time fluctuation of the power grid load and new energy power generation power prediction data; generating a supply-demand imbalance characteristic quantity of the power supply and the load; sa2, according to the supply and demand imbalance characteristic quantity, constructing a multi-objective optimization model containing participation of an energy storage system and an adjustable load; sa3, outputting a regulation and control instruction set by solving the multi-objective optimization model; and Sa4, carrying out coordination control on the source network load storage resources according to the regulation and control instruction set so as to realize dynamic balance. The method can solve the problem of how to regulate and control the new energy generation power according to the real-time fluctuation of the power grid load so as to solve the problem of mismatching between the power supply output and the load demand, thereby ensuring the stable power supply.

The invention relates to the technical field of intelligent terminals, in particular to an intelligent screen multi-terminal collaborative interaction system and method based on edge computing. The intelligent screen multi-terminal collaborative interaction system based on edge calculation comprises a terminal display unit, an edge calculation unit and an intelligent screen display unit, according to the method, feature information is extracted by integrating multiple factors, terminal display requirements and importance are accurately reflected, important information is judged according to priority permission levels, judgment is performed according to the feature information when the levels are the same or no level exists, the result is more reasonable, random or average distribution display is avoided, meanwhile, the memory occupancy rate of the smart screen is monitored in real time, and the user experience is improved. In addition, the historical information features are continuously updated, and the intelligence and adaptability of the whole system are improved.

The invention discloses a distributed power supply-containing power distribution network coordinated scheduling method, which relates to the field of power distribution network coordination, and comprises the steps of S1, multi-flexibility resource refined modeling and interaction characteristic analysis, S2, power distribution network linear load flow calculation and sensitivity analysis, and after the power distribution network linear load flow calculation and sensitivity analysis in S2 are completed, carrying out power distribution network coordinated scheduling. And S3, generating an uncertainty scene based on the generative adversarial network. According to the coordinated dispatching method for the power distribution network containing the distributed power supply, differences of various resources in control modes, response speeds and adjusting capabilities are analyzed through refined modeling, complementary characteristics of the resources are fully utilized by a collaborative optimization model, an overall optimization effect is achieved, a single type of resources are not optimized in an isolated mode, and the method is suitable for large-scale popularization and application. All adjustable resources such as a distributed power supply, an energy storage system, a reactive power compensation device, a flexible load and an intelligent soft switch are incorporated into a unified modeling and optimizing framework, and deep fusion and collaborative interaction of flexible resources can be realized.

The invention relates to the field of digital data processing, and discloses a virtual display interaction system and method based on meta universe, and the method comprises the steps: capturing a weak interaction leading signal of a user in real time, converting the weak interaction leading signal into an interaction intention primitive carrying main body, target, action and intensity information through a lightweight rule, and broadcasting the interaction intention primitive; and each client integrates the elements to construct a dynamic interaction intention flow field, so that relevant data are preloaded prospectively, and fine auxiliary regulation and control are carried out on high-intention collaborative interaction. According to the method, the interaction intention flow field is used for estimating the group trend, intelligent preposition of resources and precise assistance of cooperation are achieved, virtual feedback time delay is remarkably shortened, and the success rate and naturalness of a complex cooperation task are improved.

The invention discloses an intelligent blasting platform which comprises a physical layer, a data layer, a business logic layer, a function module layer and a user interaction layer. The physical layer is provided with an unmanned aerial vehicle, a GNSS receiver, a blasting recorder and Internet of Things sensing equipment, and blasting engineering three-dimensional geographic space information and a BIM model are generated through three-dimensional live-action modeling and BIM forward modeling; the data layer integrates GIS data, BIM data, monitoring data and engineering data, and constructs a data resource center comprising a time sequence database and a knowledge graph database; the business logic layer comprises a GIS + BIM + IoT information sensing module, a multi-source data fusion module, a blasting design module, an intelligent optimization module, a monitoring identification module and a blasting effect evaluation module; the functional module layer develops a 3D visual query module, a dynamic monitoring module, a blasting design module, an intelligent optimization module, a statistical analysis module, a forecasting and early warning module and a system management module through a front-end and rear-end separation architecture; and the user interaction layer realizes multi-terminal cooperative interaction based on WebGL, Vue3 and a mobile terminal technology.

The invention relates to the technical field of enterprise ESG digital management, in particular to a sustainable management ESG platform. The platform comprises a data access layer, a twin modeling layer, an intelligent analysis layer, a report generation layer and a collaborative interaction layer. The data access layer is used for standardized acquisition, cleaning and block chain evidence storage of multi-source ESG data; the twinborn modeling layer constructs enterprise ESG digital twinborn bodies through index mapping and scene simulation; the intelligent analysis layer realizes index dynamic monitoring, abnormity early warning and risk quantitative evaluation based on time sequence prediction and causal reasoning; the report generation layer outputs a compliance report through a multi-template automatic adaptation and natural language generation technology; and the collaborative interaction layer realizes multi-role data sharing, task tracking and strategy optimization. According to the method, multi-modal data fusion and an intelligent algorithm are fused, the efficiency of ESG data integration, risk response, report generation and collaborative management is comprehensively improved, and the problems of data isolation, response lag and manual dependence in a traditional mode are effectively solved.

The invention belongs to the technical field of optical storage and charging collaborative interaction, and particularly relates to a microgrid regulation capability evaluation system and method based on optical storage and charging collaborative interaction, and the system comprises a multi-source data fusion module, a dynamic evaluation module, a collaborative optimization module, a digital twin verification module and an output regulation and control module. The signal output end of the multi-source data fusion module is connected with the dynamic evaluation module, the signal output end of the dynamic evaluation module is connected with the collaborative optimization module, and the signal output end of the collaborative optimization module is connected with the digital twin verification module. And the signal output end of the digital twin verification module is connected with the output regulation and control module. And the mixed spatio-temporal data fusion technology reduces the synchronization error of the multi-source data. And a dynamic evaluation-optimization combined solving method is adopted, so that the calculation complexity is reduced. According to the event-driven rolling optimization mechanism, the photovoltaic output volatility and the load abrupt change rate are defined as trigger threshold values, only the affected subsystem is re-evaluated, and the calculation amount is reduced.

The invention discloses a dynamic target tracking method based on LBP (Local Binary Pattern) features and semantic features, and the method can accurately predict and reduce a first search area through the calculation of the offset of a target in an inter-frame image, the introduction of a motion amplification coefficient, uncertainty estimation and other technologies, and reduces the interference of background information on the target while reducing the calculation amount. According to the method, the target features are extracted through ResNet-50, the target features are subjected to dimensionality reduction processing while the discrimination capability and robustness of the target features are guaranteed, and the problems that the calculation amount is too large and the complexity is high are effectively avoided. Through accurate positioning and reduction of a first search area where a target is located and robust feature extraction and cooperative interaction, the ability of continuously and stably tracking the target under the complex conditions that target movement is difficult to fit, the illumination condition is complex, the target is shielded and the like is enhanced.

The invention discloses a synergy control method for a confluence area based on Rainbow DQN and a driving risk field, relates to the technical field of traffic safety, and aims to solve the problems that the overall traffic quality of mixed traffic flow is reduced and the confluence risk is increased due to the fact that a control logic is not matched with a real-time risk in an existing signal control method for the confluence area of an expressway. According to the invention, by considering the CAV-containing mixed traffic flow of the main line of the confluence area, the main line traffic flow information and the ramp queuing information, the state space and the action space of the cooperative control agent are designed in a refined manner, and a reward function considering the traffic efficiency, the traffic safety and the cooperative interaction is provided; therefore, the main line speed limit value can be dynamically controlled, the ramp queuing vehicles are dynamically coordinated, the main line CAV vehicle driving track is induced, and the passing efficiency and the traffic safety are effectively improved. The overall traffic quality of the mixed traffic flow is ensured, and the confluence risk is reduced.

The invention relates to the technical field of power grid energy storage regulation and control, in particular to a power grid energy storage regulation and control method and system considering source-storage-load collaborative interaction. The power transmission node information of the power grid system and the power utilization information of each terminal user are acquired, the power grid system is divided into a plurality of virtual energy storage clusters according to the power transmission node information, and load fluctuation characteristic analysis is performed on the power utilization data of all the terminal users of each virtual energy storage cluster; determining a first importance degree of each load area to the electric energy demand; obtaining a second importance degree of each load area in an abnormal state according to the load power change before and after the power generation fault; and according to the first importance degree and the second importance degree of each load area, correspondingly configuring the electric energy guarantee priority of each load area and supplying power until the power generation fault is repaired. According to the technical scheme, after the power grid system has a power generation fault, cooperative adjustment of the energy storage station, the power supply station and the load end is realized, and the accuracy of electric energy distribution is effectively improved.

The invention discloses a multi-modal remote sensing small target recognition method based on common-differential mode collaborative interactive fusion, and relates to the technical field of image recognition. Performing feature extraction and interactive fusion based on a double-flow backbone feature extraction network in the multi-modal remote sensing small target recognition model to obtain an infrared enhanced fusion feature and a visible light enhanced fusion feature respectively; the infrared enhancement fusion features and the visible light enhancement fusion features output by the corresponding convolution down-sampling module and the output layer in the two backbone feature extraction channels are spliced and then are subjected to neck feature fusion output to obtain a prediction image with a target recognition result. According to the method, infrared and visible light modal features are fully utilized, and common features and difference features of the infrared and visible light modal features are subjected to collaborative modeling and interactive fusion, so that the characterization level of the small target is effectively improved, and recognition of the remote sensing small target is more robust.

The invention discloses an intelligent unmanned remote control system and method for an oil field electric workover rig, and relates to the field of remote control of the oil field electric workover rig, and the system comprises a full-dimension sensing network construction module, a digital twin driving cognition module, an edge intelligent decision module, and a man-machine co-fusion interaction module. According to the intelligent unmanned remote control system and method for the electric workover rig in the oil field, a three-level decision-making tree designed by dynamic priority task scheduling sets extremely short response time for different level requirements of emergency braking, working condition adjustment and parameter optimization, various sudden and conventional operation change conditions can be rapidly dealt with, and the operation efficiency is improved. By establishing a comprehensive multi-objective optimization function, energy consumption, operation time and risk indexes can be comprehensively considered, weight coefficients can be flexibly adjusted according to different operation scenes and user requirements, and equipment operation parameters and operation process control schemes which meet multi-objective optimization and conform to equipment and operation safety and performance constraint conditions can be accurately searched.

The invention provides an agent collaborative interaction method and system and electronic equipment. The agent collaborative interaction method comprises the following steps: registering agent capability information to a network registration function network element; sending a first service retrieval request to the network registration function network element according to the current task, and receiving a first retrieval result returned by the network registration function network element; when the first retrieval result comprises at least one service party agent, determining state information of the service party agent according to the first retrieval result, and selecting the service party agent to send a service negotiation request; when it is determined that a service negotiation response returned by the service party agent based on the service negotiation request is received, sending a co-processing data packet corresponding to the current task to the service party agent through an interaction mode corresponding to the service negotiation response; and receiving a co-processing result corresponding to the co-processing data packet returned by the service agent, and processing the current task according to the co-processing result. According to the embodiment of the invention, the agent interaction efficiency can be improved.

The invention relates to the technical field of emotion monitoring and adjusting, and discloses an emotion monitoring and adjusting system based on real-time dialogue semantic analysis, and the system is characterized in that an information collection module is used for collecting real-time voice information of two dialogue parties; the real-time dialogue semantic analysis module is used for performing semantic analysis on real-time voice information by adopting a MobileViT network, extracting emotional characteristics and dynamically capturing emotional association in a dialogue in combination with a CSN network; the bidirectional emotion regulation module is used for determining the current emotion state of the user based on the output of the real-time dialogue semantic analysis module, mapping the emotion state to a behavior mode, and respectively generating personalized emotion regulation strategies for two dialogue parties by adopting a Bandit algorithm; the hardware and software collaborative interaction module is used for controlling the bone conduction equipment and the LED feedback device according to the emotion regulation strategy generated by the bidirectional emotion regulation module; through cooperative work of software and hardware, real-time monitoring and effective adjustment of emotions of two parties of a dialogue are realized.

The invention relates to the technical field of robots, in particular to a mobile robot remote operation system and method based on mixed reality, and the method comprises an operator end and a robot end, the operator end completes a complex remote operation task based on visual feedback provided by a man-machine cooperation interaction interface, and the robot end completes a remote operation task based on visual feedback provided by the man-machine cooperation interaction interface. The virtual reality controller integrates a motion state and an operation mode of the mobile robot, and the mixed reality server generates visual feedback according to visual information of a remote operation visual angle of the mobile robot; the robot end comprises a mobile robot, a collection device on the mobile robot and a robot server, and after the mobile robot receives a remote control instruction sent by the virtual reality controller to the robot end, posture and button information of the mobile robot are input into the robot server to drive the mobile robot to move. Therefore, the problems of low real-time performance and accuracy of remote control, poor operation efficiency and flexibility and the like caused by limitation of bandwidth and system time delay in related technologies are solved.

The invention provides a multi-agent collaborative interaction method and device, a computer storage medium and electronic equipment, and relates to the technical field of artificial intelligence. The method comprises the following steps: carrying out relevancy judgment on received to-be-processed information and multiple pieces of interactive context information; in response to the condition that the relevancy between the to-be-processed information and the target interaction context information is greater than a relevancy threshold value, labeling a target theme identifier which is the same as the target interaction context information for the to-be-processed information; and sending a first task processing request for the to-be-processed information to a second agent in the plurality of agents, so that a large model of the second agent obtains target interaction context information according to a target theme identifier contained in the first task processing request, and processes the to-be-processed information based on the target interaction context information. According to the method, the processing information amount of the large model can be reduced, the system performance pressure is relieved, and part of interaction information is prevented from being discarded, so that the output quality of the large model and the intelligent agent scheduling performance are improved.

Systems and methods relate to executing a task using a machine learning model based on prompt generation and collaborative interactions with a user. The machine language model generating a set of questions based on a task request. The user interactively answers the questions. A task processor generates a set of question-answer pairs based on the questions generated by the machine learning model and the answers given by the user. The machine learning model generates a task specific output based on the set of question-answer pairs. The machine learning model represents a large language model with deep learning. The simple question-and-answer prompts enable non-expert users to instruct the machine learning model with information that is sufficient to execute the task without overwhelming the users with the operations. The machine learning model leverages the answers to execute the task with accuracy, thereby providing efficacy of the prompting technique.

The invention discloses an interactive computer programming teaching intelligent practical training platform and a construction method, and the platform comprises a practical training platform terminal, a multi-modal data collection module, a dynamic knowledge graph module and a dual learning module, the multi-modal data collection module is used for synchronously capturing a code editing event stream, biological characteristic data and a cooperative interaction log; the dynamic knowledge graph module is used for establishing an association network through an incremental graph updating algorithm, and the bidirectional reinforcement learning module is used for collaboratively optimizing instant feedback quality and long-term learning path planning of programming teaching through a hierarchical decision-making mechanism; code operation, biological characteristics and collaborative data are captured in real time through a multi-modal data acquisition system, and collaborative optimization of instant feedback and long-term path planning in a programming teaching process is realized by combining incremental association network construction of a dynamic knowledge graph and a hierarchical decision mechanism of dual reinforcement learning; the cognitive state is accurately evaluated through eye movement tracking and keyboard behavior analysis.