A study of Temperal Difference Learning using Nonlinear Function Approximation

비선형 함수 근사화를 사용한 TD학습에 관한 연구

  • Published : 1998.11.28

Abstract

This paper deals with temporal-difference learning that is a method for approximating long-term future cost as a function of current state in knowlege-poor environment, a function approximator is used to approximate the mapping from state to future cost, a linear function approximator is limited because mapping from state to future cost has a nonlinear characteristic, so a nonlinear function approximator is used to approximate the mapping from state to future cost in this paper, and that TD learning using a nonlinear function approximator is stable is proved.

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