4 results about "Cognition.knowledge" patented technology

The invention discloses an education content recommendation method and system based on group intelligence, and the method comprises the steps: constructing a user dynamic cognition knowledge graph, and carrying out the dynamic attenuation of the memory intensity attribute of a knowledge point node based on a cognition forgetting model in combination with the memory stability; defining utilization pheromones on edges of the knowledge graph, and strategically injecting exploration pheromones according to forgetting states of users or knowledge breadth indexes; guiding a swarm intelligence algorithm to construct a learning path according to a rule jointly influenced by bimodal pheromones; and finally determining an optimal path and generating recommendation. According to the method, accurate intervention on a learning process and intelligent guidance on knowledge exploration are realized through deep fusion of a recognition scientific model and a swarm intelligence algorithm of bimodal pheromones, the learning stability is remarkably improved, information cocoon houses are effectively broken, and the interpretability of recommendation is enhanced through path intention analysis.

The invention discloses an analysis system and method oriented to man-machine cooperation. The system comprises a knowledge center, a meta logic learning unit, a complex task decomposition unit, a machine cognitive logic evolution unit, an intelligent algorithm library, a cognitive logic library, an expert thinking module and a historical case library. The knowledge center comprises an object knowledge model, a task knowledge model, a rule knowledge model and a cognitive knowledge model; the element logic learning unit comprises an element logic module and a learning module; the complex task decomposition unit receives a target task, calls knowledge center data to decompose the target task, and performs meta-logic mapping based on the meta-logic module; the machine cognitive logic evolution unit combines the element logics obtained through mapping, logic abstract calculation is conducted on the combined element logics, and cognitive logics of the corresponding types are obtained. According to the invention, the intelligent level and man-machine cooperation efficiency of the intelligent processing analysis equipment and system are improved.

This application provides an intelligent recommendation and decision-making method and system based on graph neural networks and cognitive architecture. The method includes: performing situational awareness knowledge reasoning based on the agent's detection data of the current environmental state to obtain a situational awareness structure; performing task planning knowledge reasoning on the situational awareness structure to obtain all matching task planning rules, and generating an operator structure based on each matching task planning rule; the operator structure representing the agent's actions; using a graph neural network-based intelligent recommendation model to perform matching degree reasoning on the situational awareness structure and the operator structure to obtain dynamic preference values ​​for the operator structures; and selecting the optimal operator structure based on the dynamic preference values ​​of each operator structure to determine the decision action. This solution can solve the problem of insufficient robustness in unmanned systems using cognitive architecture for decision-making, improve the reliability of intelligent agent decision-making, and can be widely applied in the field of intelligent decision-making technology for autonomous mobile systems.

This invention discloses a method and system for recommending educational content based on swarm intelligence. The method includes: constructing a dynamic cognitive knowledge graph for users, where the memory strength attribute of knowledge point nodes is dynamically decayed based on a cognitive forgetting model and combined with memory stability; defining pheromones on the edges of the knowledge graph and strategically injecting exploration pheromones according to the user's forgetting state or knowledge breadth index; guiding a swarm intelligence algorithm to construct learning paths based on rules jointly influenced by bimodal pheromones; and finally determining the optimal path and generating recommendations. This invention, through a deep integration of cognitive science models and a bimodal pheromone-based swarm intelligence algorithm, achieves precise intervention in the learning process and intelligent guidance for knowledge exploration, significantly improving the stability of learning, effectively breaking down information cocoons, and enhancing the interpretability of recommendations through path intent analysis.