Design and Research of Agent-based Personalized Recommendation System

In recent years, with the continuous development of multi-agent technology and distributed artificial intelligence, the requirement for agents to have autonomous decision-making ability is also getting higher and higher. The application of multi-agent technology to the decision-making of complex problems under distributed structure has become an important research direction. This paper mainly studies the design of agent-based personalized recommendation system. This paper first analyzes the concept of agent, and expounds the basic model of collaborative filtering algorithm. On this basis, a multi-agent based recommendation framework model is designed, which uses multiple agents to build a large and complex system into a small subsystem that communicates and coordinates with each other and is easy to manage. This paper makes an experimental analysis of the constructed model. Through the experimental results, we can know that the performance of the multi-agent recommendation model constructed in this paper is better than the other two models.