2 results about "Cognition.knowledge" patented technology

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.