A multi-agent learning model based on dynamic fuzzy logic

Machine learning is one of the key problems of artificial intelligence, and the agent learning has become an important branch of machine learning. One of the main characters of intelligence agent is that it can adapt to the unknown environment. The ability to learn is the key property of agent. Because the learning act of agent is dynamic and fuzzy, this paper uses the conception of dynamic fuzzy logic. First, it gives the conception of agent learning based on DFL. Then, it supplies a multi-agent learning model based on DFL, namely a multi-agent learning model planned on a whole. Furthermore, the paper validates that the model is an useful model by an example.