Similarity between Fuzzy Multi-objective Control and Eligibility

Abstract

A fuzzy multi-objective control problem has been handled in many different ways such as neural network and reinforcement learning etc. Among them, reinforcement learning solves a fuzzy multi-objective control problem without any priori knowledge about an environment. In this paper, a new method of reinforcement learning for a fuzzy multi-objective control problem is proposed in consideration of newly defined objective TD( λ ), where TD stands for a temporal difference. The proposed method reformulates a fuzzy multiobjective control problem into a problem similar to a reinforcement learning problem under non-Markov environment, where objective eligibility is considered for handling multi-rewards, similarly as TD( λ ) is applied to a reinforcement learning problem under a non-Markov environment.