Evolutionary Learning, Reinforcement Learning, and Fuzzy Rules for Knowledge Acquisition in Agent-Based Systems


The behavior of agents in complex and dynamic environments cannot be programmed a priori, but needs to self-adapt to the specific situations. We present some approaches based on evolutionary, reinforcement learning algorithms, able to evolve in real-time fuzzy models that control behaviors. We discuss an application where an agent learns how to adapt its… (More)


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