211 results about "Knowledge content" patented technology

The invention discloses an intelligent customer service system based on an AI large model, and belongs to the technical field of intelligent customer service systems. Through the multi-modal interaction technology, the flexibility of the system and the user experience are improved, the data type is intelligently recognized and correspondingly processed, the language style and emotional intonation of the response content are automatically adjusted according to the mood and intention of the user, the knowledge base integrates static data and dynamic interaction data, and the user experience is improved. Real-time updating and comprehensiveness of knowledge content are ensured, rapid retrieval is performed based on a knowledge base, accurate reply is performed in combination with a large language model, high-quality answers and solutions are generated through rule reasoning and model generation, state information of each round of interaction of a user is recorded and managed by constructing a dialogue state tracker, and the user experience is improved. And precise tracking and updating of the context are realized. For a complex task, the system splits a user request into a plurality of sub-tasks, and the sub-tasks are executed in sequence according to the priority and the dependency relationship, so that the high efficiency and continuity of task processing are ensured.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of medical health, financial science and technology, culture research and the like, and discloses a content generation and optimization method based on a knowledge graph, which comprises the following steps: constructing a multi-source knowledge database, extracting core concepts and knowledge contents, and constructing the knowledge graph. Performing semantic analysis to generate semantic vector representation and a keyword list; retrieving the associated text fragment based on the semantic vector and the keyword list, and inputting the associated text fragment into a generation model to generate initial answer content; and utilizing the knowledge graph to match the domain entity and the knowledge graph node, generating a logical reasoning path, optimizing the initial answer content, and generating the final answer content. According to the method, content generation of accurate retrieval, deep knowledge association and logical reasoning enhancement is realized by fusing a multi-source knowledge database, knowledge graph reasoning and generation optimization; semantic vector matching and keyword retrieval are combined, so that the accuracy of knowledge acquisition is improved; and through knowledge graph reasoning path construction, the answer logic is coherent.

The invention relates to the technical field of data processing, and discloses an AI knowledge base construction method and system for intelligent water conservancy. The method comprises the following steps: forming a water conservancy intelligent perception data set by integrating hydrological monitoring data, engineering operation records and expert literatures; knowledge sprouts are identified, and a water conservancy native knowledge unit is generated; key features are extracted, knowledge element decomposition is carried out, and a knowledge evolution chain network is constructed through correlation analysis; screening in combination with a historical application effect and expert evaluation to obtain a preferred knowledge body; performing intelligent reconstruction on a scheduling rule, risk prevention experience and an operation and maintenance method to form an innovative knowledge base; and finally, intelligently matching with real-time engineering requirements to generate an intelligent water conservancy AI knowledge base. According to the application, by establishing a self-adaptive knowledge acquisition, organization and application mechanism, the knowledge base can autonomously update the knowledge content according to the environment change, the knowledge structure is optimized, and the intelligent operation management level of the water conservancy project is improved.

The invention specifically relates to the technical field of natural language processing, and discloses an intelligent interactive customer service system based on an AI large model, which comprises a multi-modal input analysis module, an intention preliminary detection module, a large model semantic understanding module, a dynamic knowledge base association module, a dialogue strategy generation module, a natural language generation module and a service feedback work order module, through deep cooperation of a multi-modal input analysis module and a large model semantic understanding module, entity and attribute information is accurately extracted, context semantic association information is mined, and through the cooperative effect of an intention preliminary detection module, a dynamic knowledge base association module and a dialogue strategy generation module, based on a semantic analysis result output by a large model, a dialogue strategy is generated. According to the method and the system, matching calculation is carried out with the constructed dynamic knowledge base, rich knowledge support is provided for solving complex problems, personalized knowledge content is recommended for different users through the natural language generation module and the service feedback work order module, and the reply matching degree and the complex problem processing capacity are greatly improved.

The invention discloses an emergency fire fighting question answering method and system based on the AI large language model technology and a storage medium, and relates to the technical field of artificial intelligence, the emergency fire fighting question answering system comprises a front-end module, an AI preprocessing thread pool, a knowledge base module and a large model calculation engine module, the AI preprocessing thread pool receives a service request sent by the front-end module, and sends the service request to the AI preprocessing thread pool; different task threads are distributed, a knowledge base of a corresponding region category is automatically called according to the region category input by a service request to perform content similarity retrieval, knowledge content data obtained through retrieval and the corresponding service request are sorted and then uniformly sent to the large model calculation engine module supporting parallel processing to perform analysis and calculation, and the large model calculation engine module is used for performing analysis and calculation on the knowledge content data and the corresponding service request. By using the technical means of the invention, the user does not need to think what the keyword of the current question is, and can completely organize the question, directly ask the question, automatically query the local professional knowledge base and give professional and accurate answers according to the actual situation of the site, so that real barrier-free communication is realized.

The invention provides a knowledge data classification multi-modal reasoning evolution system based on a deep model, and the system comprises a dynamic semantic memory network module which is used for storing multi-source heterogeneous data through a memory network, and according to the relevance between the newly input multi-source heterogeneous data and the existing knowledge content in the memory network, obtaining the knowledge content of the multi-source heterogeneous data; dynamically updating the knowledge content in the memory network; the cross-modal collaborative classification enhancement module is used for extracting feature vectors of different modals from the multi-source heterogeneous data, performing feature alignment, and performing feature fusion on the feature vectors after feature alignment to generate comprehensive feature vectors fused with multi-modal information; and the multi-level layered attention classification module is used for processing the comprehensive feature vector by adopting a multi-level attention mechanism to understand the overall content and context information of the multi-source heterogeneous data so as to make a classification decision. According to the method, intelligent processing and classification decision making of complex information are realized, and a solid technical support is provided for knowledge evolution of a Chinese graph classification system.

A content interaction method and apparatus, a readable medium, an electronic device and a program product, the content interaction method comprising: obtaining target content input by a target user in an intelligent object page, the intelligent object page being used for interaction between the user and an intelligent object; first reply content is generated at least based on the target content and a virtual human cue word through a first machine learning model associated with the intelligent object, and the virtual human cue word is used for enabling the first machine learning model to generate anthropomorphic reply content; and performing knowledge content recall based on the target content through a second machine learning model associated with the intelligent object to obtain target knowledge content, and generating second reply content based on the target knowledge content, the second reply content being used for answering a question corresponding to the target content. The time delay of receiving reply content by a user can be reduced, the flexibility of the reply content is improved, and the interaction experience of the user is improved.

The invention discloses an intelligent document generation system and method for bidding documents, and the system comprises a preprocessing module which is used for obtaining bidding document files in various formats, and converting the obtained bidding document files in various formats into structured bidding document files; the analysis module is used for analyzing the converted bidding document file based on the large model cue word to obtain a structured bidding document file analysis result; the directory generation module is used for generating a directory of the bidding document file according to the analysis result; the retrieval module is used for generating a corresponding knowledge content set according to the bidding document file directory; and the content generation module is used for generating the text content of the bidding document file based on the knowledge content set and the structure information of the bidding document file directory. And the content assembly module is used for performing multi-dimensional feature extraction and classification on the generated bidding document file text content, and completing content assembly according to a preset document structure tree to obtain a standard document meeting bidding document requirements.

The invention discloses an online knowledge base platform for ensuring knowledge content quality and contributor rights and interests and a business model of the online knowledge base platform, and relates to the field of online knowledge bases. The platform integrates block chains, data encryption and artificial intelligence technologies, and aims to improve the quality of knowledge content and protect the rights and interests of contributors. The platform mainly comprises a block chain system, a data encryption system, an artificial intelligence system, a member management system, an auditor evaluation system, a knowledge content collection system, a knowledge content auditing system, an incentive management system, a template management system, a fund management system, a suggestion supervision system, a point transaction system, an advertisement management system and the like. Through a decentralized knowledge management mechanism, a contributor auditing and evaluating mechanism, a knowledge content providing and auditing mechanism and a contributor right protection mechanism, high quality of knowledge base content and fair reward of contributors are ensured, and sharing and communication of knowledge are promoted.

The invention discloses a cloud management and intelligent distribution method for classroom teaching resources, and relates to the technical field of cloud computing software. The classroom teaching resource cloud management and intelligent distribution method comprises the steps that S1, multi-source teaching resource data and auxiliary distribution data are acquired and preprocessed, and a knowledge content database is constructed; s2, performing semantic fusion analysis through text semantic association, structural consistency and professional term coverage data; s3, carrying out dependency evaluation by fusing pre-association, knowledge co-occurrence, sequence association and semantic fusion data; s4, performing resource adaptability distribution analysis through the maximum knowledge dependence value in combination with the learning state data and the historical feedback data; and S5, evaluating the teaching resource quality by collecting classroom feedback, teacher evaluation and resource use data, and implementing content optimization. The problems of semantic distortion, path breakage, distribution mismatching and resource updating inconsistency in the teaching resource data fusion and intelligent resource distribution process are solved.

The invention relates to the technical field of health assessment, and discloses a user climacteric physical and psychological health assessment and science popularization system, which comprises a science popularization plot and dynamic assessment process module, a multi-dimensional assessment engine and a general knowledge and personalized knowledge content push engine which are in closed-loop communication connection in sequence. According to the application, the science popularization garden and dynamic evaluation process module not only ensures data integrity, but also adapts to real-time updating requirements of medical guidelines; the multi-dimensional assessment engine fuses the multi-dimensional data and processes the medical scale, so that more comprehensive and accurate health assessment is realized; a general knowledge and personalized knowledge content pushing engine constructs a dynamic user portrait based on multi-dimensional data and evaluation results, and realizes accurate matching and interpretable pushing of health knowledge through a tag system and a four-dimensional evaluation system; the flexibility and the operation efficiency of the evaluation system and the acceptability of the user to the health management content are improved, and a finer and more efficient physical and psychological health doctor-patient management scheme is provided for climacteric people.

The invention relates to the technical field of dialogue robots, and provides a big language model dialogue robot-based data processing method and related equipment, and the method comprises the steps: carrying out the text conversion and vectorization processing of voice input content, and obtaining text data and vector representation; performing similarity retrieval on the vector representation and vector data in a preset vector database to obtain associated knowledge content; performing keyword and key demand screening on the text data to generate cue words, and inputting the associated knowledge content and cue words into a preset large language model to generate a natural language answer text; and converting the natural language answer text into voice information and outputting the voice information. Through the scheme, the understanding of the voice input content of the user and the generation of the natural language answer are realized, and the problems of time and labor consumption in knowledge base construction and mechanization of the dialogue content due to the fact that an existing dialogue robot extracts predefined content or pre-recorded text from a knowledge base to answer the user are solved.

The invention provides an enterprise-level unstructured knowledge governance-oriented method and a storage medium. The method comprises the steps that an initial document is input into a visual language model for layout analysis, and document structure information of a target document is obtained; segmenting the document structure information to generate text slices to be vectorized; metadata extraction is carried out based on the text slices, and structured knowledge content vectors are generated; and performing index configuration according to the knowledge content vectors to form enterprise-level knowledge governance standards. According to the method, the document structure is analyzed through the visual language model, the text slices are generated through the intelligent segmentation algorithm, the knowledge vector is constructed through metadata extraction, and the mixed index configuration is performed, so that the problems of inaccurate layout analysis, logic structure damage and low retrieval efficiency in the traditional technology are effectively solved, and the method has the advantage of improving the knowledge management precision and availability.

The invention relates to a knowledge question and answer method and device and a storage medium. The knowledge question-answering method comprises the steps of obtaining an original knowledge text and question-answering data input by a user; performing extraction processing on a content abstract in the original knowledge text to obtain a first text fragment; feature extraction is conducted on the first text fragment, feature vectors are obtained, and the feature vectors comprise keyword feature vectors, problem feature vectors and text fragment feature vectors. And creating a key value pair between the feature vector and the first text fragment. And based on the key value pair and the question and answer data, determining reply data of the question and answer data. According to the invention, the understanding ability of knowledge content in the original knowledge text can be improved, and accurate reply data can be provided based on the original knowledge text for the question and answer data.

The present disclosure provides a cross-file question and answer knowledge extraction method and system, and an electronic device. The method includes: obtaining a user question; converting the user question into a user question embedding vector by using an embedding function; determining the user question embedding vector and a first similarity vector of a root node of a file embedding vector tree of each professional knowledge file; determining a plurality of similar vector trees by using a K-nearest neighbor algorithm based on first similarity vectors of all root nodes; determining a candidate node set by using the K-nearest neighbor algorithm based on all the similar vector trees; determining an optimally-matched node set based on the candidate node set; and determining, based on the optimally-matched node set, file knowledge content corresponding to the user question. The present disclosure improves accuracy of extracting the cross-file question and answer knowledge.

The embodiment of the invention discloses a service information generation method and device, equipment and a medium, and the method comprises the steps: obtaining to-be-replied service dialogue information, and determining corresponding service interaction state information according to the to-be-replied service dialogue information and corresponding historical service dialogue information; performing knowledge content matching in a preset business knowledge base according to the business interaction state information, the to-be-replied business dialogue information and the historical business dialogue information to obtain business interaction prompt information; and inputting the to-be-replied service dialogue information and the service interaction prompt information into a service interaction information generation model to obtain service reply information corresponding to the to-be-replied service dialogue information. According to the technical scheme provided by the embodiment of the invention, the problem of low dialogue quality of an artificial intelligence customer service in a business interaction process is solved, the dialogue fluency and semantic accuracy of an artificial intelligence robot in the business interaction process can be improved, the illusion probability of an output result of an artificial intelligence model is reduced, and the business progress is smoother.

The invention provides a periodical knowledge graph construction method, a periodical knowledge question-answering method and a periodical knowledge graph construction device. The periodical knowledge graph construction method comprises the following steps: performing sequence labeling method knowledge extraction on an obtained periodical text to be processed to obtain a knowledge labeling sequence; performing vocabulary network strategy entity alignment on the knowledge labeling sequence to obtain an aligned knowledge sequence, performing priority strategy entity disambiguation on the aligned knowledge sequence to obtain a disambiguation knowledge sequence, and performing knowledge reasoning completion on the disambiguation knowledge sequence to obtain integrated journal knowledge; and performing knowledge graph construction according to the integrated periodical knowledge to obtain a periodical knowledge graph. Primary knowledge extraction is carried out through a sequence labeling method, knowledge entities of different data sources are aligned through a vocabulary network strategy, periodical knowledge of different sources can be effectively integrated, ambiguous content between entities is eliminated through priority strategy entity disambiguation, missing values and blank values are complemented through knowledge reasoning, the knowledge content can be effectively verified, and the accuracy of the periodical knowledge is improved. Therefore, the data quality of the periodical knowledge graph is improved.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses a dynamic state portrait driven service optimization method, device and equipment and a medium. And constructing a dynamic state portrait of the individual, analyzing the state portrait to generate a state abnormality level, adjusting strategy optimization service parameters according to the state abnormality level and the service parameters, and matching knowledge contents based on the state data and the abnormality level to output guidance information. According to the method, the multi-source state data of the individual is integrated, the state portrait is dynamically constructed, and the state abnormal level is identified, so that the self-adaptive adjustment of the service parameters and the personalized matching of the knowledge content are realized, and the timeliness and pertinence of service customization are improved.

The invention discloses an artificial intelligence question answering system and method based on multi-knowledge-base association. The method comprises the following steps: acquiring a question input by a student; preprocessing the questions, including operations of word segmentation, part-of-speech tagging, stop word removal and the like; identifying a plurality of knowledge points and themes involved in the questions; associating a plurality of related knowledge bases based on the identified knowledge points; carrying out vectorization processing on the questions and the content in the knowledge base, and constructing high-dimensional vector representation; matching the question vector with the knowledge base vector by using a vector database, and retrieving knowledge content most relevant to the question; based on the retrieved knowledge content, adopting a generative pre-training model to generate a high-quality answer; and feeding back the generated answer to the student, and collecting the evaluation and feedback of the student on the answer to continuously optimize the system performance. According to the method, complex questions related to multiple knowledge points can be effectively processed, and the matching degree and the answering quality of the question answering system are improved through a multi-knowledge-base association and vectorization matching method. According to the method, the limitation of a single knowledge base and simple text slice reasoning in the prior art is overcome, the artificial intelligence question-answering system has higher intelligence and adaptability, and the constantly changing requirements in the education field are better met.

The invention provides a dialogue response method and device, electronic equipment, a storage medium and a product, and the method comprises the steps: determining a reply bedding verbal skill corresponding to dialogue content based on the dialogue content inputted by a user, and carrying out the knowledge acquisition of the dialogue content, and obtaining the knowledge content corresponding to the dialogue content; transmitting the reply bedding verbal skill to the man-machine interaction end to enable the man-machine interaction end to output the reply bedding verbal skill, and performing continuous writing on the reply bedding verbal skill based on the knowledge content to obtain dialogue reply information corresponding to the dialogue content; and transmitting the dialogue reply information to the man-machine interaction end, so that the man-machine interaction end outputs information except the reply underlay verbal skill in the dialogue reply information. According to the scheme, the reply bedding verbal skill can be generated and output while the knowledge content is obtained, then the reply bedding verbal skill is continuously written to obtain and output the dialogue reply information, and when the dialogue reply information is not generated, the reply bedding verbal skill is firstly output to respond to the dialogue, so that the dialogue response efficiency and the user experience effect are improved.

The invention discloses a knowledge space control method and system for assisting learning, and relates to the technical field of knowledge space generation methods, and the method comprises the steps: determining a corresponding problem solving path according to the previous problem solving content of a user; and determining error contents of each problem solving node in the problem solving path based on matching of the problem solving path and the knowledge application space, and marking knowledge nodes associated with the error contents. Determining corresponding correct content according to the error content and knowledge content presented by the knowledge node, determining difference content between the correct content and the error content, determining a correct answering thought according to the difference content and the answering thought of the user relative to the error content, and marking knowledge difficult points of the user; the error factors of the user are determined according to the knowledge difficult points of the user, the corresponding mastering level and the answering accuracy of the user, the corresponding auxiliary learning measures are determined based on the error factors of the user and the current learning process of the user, and the accuracy of the auxiliary learning measures is improved.

The invention provides a data acquisition method and device, electronic equipment and a product, and is applied to the technical field of model training. The method comprises the following steps: extracting a plurality of first questions and a plurality of knowledge contents from a knowledge text, and constructing a plurality of second questions according to each knowledge content; optimizing each second problem and each first problem to obtain a plurality of target problems; determining at least one piece of knowledge content corresponding to each target question, wherein the at least one piece of knowledge content corresponding to the target question comprises an answer of the target question; and according to each target question and the corresponding at least one knowledge content, constructing question and answer data corresponding to each target question, the question and answer data being used for training a model.

The invention relates to an electric power intelligent knowledge retrieval method and device based on an RAG model, computer equipment, a computer readable storage medium and a computer program product, and can be applied to the technical field of computers. The method comprises the steps of obtaining a query request; performing semantic analysis processing on the query request to obtain a query semantic feature of the query request; according to the query semantic features, candidate knowledge content is retrieved from a pre-constructed electric power knowledge base; screening the candidate knowledge content to obtain a target retrieval result of the query request; inputting the target retrieval result into a pre-trained power field content answer model for content answer processing to obtain preliminary answer content of the query request; and performing security filtering processing on the preliminary answer content to obtain a target answer result of the query request. By adopting the method, the power knowledge acquisition efficiency can be improved.

The invention relates to the field of artificial intelligence, in particular to an AI-based nursing knowledge interesting courseware generation method and system. The method comprises the following steps: firstly, constructing an AI model library, and packaging input parameters and output parameters of each AI model in the model library; the nursing knowledge is uploaded to the system; creating a corresponding abstract task for nursing knowledge, and operating an AI model to obtain high-quality knowledge key points; supplementing cue words for the knowledge key points, and providing the cue words to an AI large model to generate materials; performing structured arrangement on courseware themes, chapters and contents by applying a mind mapping method, packaging the courseware themes, chapters and contents into AI model input parameters, and performing automatic layout through the AI model to generate a PPT file; and adjusting the PPT file, outputting the PPT file as courseware, and editing and processing courseware content. The AI model technology is utilized, key knowledge content can be quickly extracted, rich teaching materials can be generated, the courseware making method is optimized, the input of teaching group course making is effectively reduced, the courseware quality is improved, and the professional level of nursing personnel can be effectively promoted to be improved.

The embodiment of the invention provides an information processing method and computing equipment. The method comprises the steps of obtaining user input content; determining a target knowledge base which can be accessed by the user in combination with the user feature information and the knowledge base feature information; searching target knowledge content matched with the input content from the target knowledge base; and generating feedback information by using a large language model according to the target knowledge content and the input content. According to the technical scheme provided by the embodiment of the invention, the accuracy of the large language model is improved, and the data security is ensured.

The invention relates to the technical field of computers, and discloses a knowledge base-based authority control method, device and equipment and a medium, and the method comprises the steps: obtaining a to-be-accessed target knowledge base and a user identity information set, and carrying out the grading processing of the knowledge content in the target knowledge base through a natural language model, and obtaining a plurality of knowledge categories; determining an initial user identifier corresponding to each piece of initial user identity information in the user identity information set, and establishing a corresponding relationship between each initial user identifier and the knowledge category; receiving an access request of a target knowledge base, determining a target user identifier from the user token information in the access request, and determining an authorized target knowledge category from the corresponding relationship according to the target user identifier; and performing legality verification on the access request, and if the verification is passed, allowing the access request to access the knowledge content corresponding to the target knowledge category. The method can be applied to financial science and technology and medical care service program systems, and fine-grained permission allocation and access verification can be achieved.

The embodiment of the invention relates to the technical field of information, in particular to an SQL resource estimation method, device and equipment based on a large model, and the method comprises the steps: receiving an SQL statement input by a user, correcting a grammar error, and outputting a correct SQL code; analyzing fields, functions and limiting conditions in the SQL codes by configuring a large language model of a Python code executor tool; python codes are automatically written according to fields and limiting conditions, an operation environment is configured and executed, the size of a source data table is read, data are screened according to the limiting conditions, and the size of a screening table is obtained; according to the static parameters of the function, retrieving the original knowledge content to obtain an original knowledge set containing the Spark principle and historical execution data; and estimating resource parameters based on the SQL static parameters, the double-table dimension information and the original knowledge set. Spark parameters are generated through principle calculation and historical verification, and accurate resource configuration, cluster management and control and multi-field application requirements are met.

The invention relates to the field of computer data processing, in particular to a guided learning assistance method, system and device and a computer readable storage medium. The method comprises the steps of obtaining to-be-learned knowledge content corresponding to a target user, wherein the to-be-learned knowledge content comprises a plurality of knowledge elements; sequentially displaying the plurality of knowledge elements to the target user in multiple rounds, so that the target user can learn the plurality of knowledge elements; wherein the display process of each knowledge element in the plurality of knowledge elements comprises the following steps: acquiring user behavior data of a target user for the currently displayed knowledge element; analyzing the user behavior data according to a preset evaluation index corresponding to the currently displayed knowledge element to obtain an evaluation result of the currently displayed knowledge element by the target user; and adjusting the knowledge elements displayed in the next round according to the evaluation result. The method can better assist the user in learning based on the feedback of the user.

The invention relates to the technical field of big data evaluation, in particular to an AI educational training analysis method and system based on big data evaluation, and the method comprises the steps: obtaining a weak link of the operation of a corresponding person from historical operation data, constructing an operation weak link knowledge point graph based on the knowledge content related to the weak link, and obtaining an AI educational training analysis result; performing weak knowledge point association analysis based on the operation weak link knowledge point graph to obtain association conditions of the weak knowledge points, and performing importance weight analysis of the weak knowledge points based on the association conditions of the weak knowledge points and the risk levels of the corresponding weak links obtained through evaluation. The course resource matching analysis is carried out based on the importance weight analysis of the weak knowledge points, the danger degree of weak links is evaluated, and the course resource matching is carried out according to the importance weight of the weak knowledge points, so that personnel can learn and master key knowledge and skills in time, and the risk of accidents caused by misoperation is reduced.

The invention discloses a teaching method and device based on an intelligent agent system, and the method comprises the steps: receiving a to-be-learned knowledge theme, expanding to-be-demonstrated knowledge content according to the to-be-learned knowledge theme, generating a demonstration mode corresponding to the to-be-demonstrated knowledge content, and demonstrating the to-be-demonstrated knowledge content through a knowledge demonstration script, the demonstration mode comprises a knowledge demonstration script generated based on the to-be-demonstrated knowledge content and the type and the number of bodies of the intelligent agent system. The method solves the problems that in the prior art, teaching content is high in presetting performance, flexibility is lacked, and knowledge innovation is not supported; the robot depends on a single type of robot, and the body language is mainly used for social contact rather than knowledge transfer; in order to solve the problems of low flexibility caused by high matching degree of a demonstration method and contents and incompatibility with robot cluster multi-modal fusion demonstration, the teaching method provided by the invention can change along with interaction between an agent with a body and a user, and the teaching diversity is increased.