Empirical Evaluation of an Average Reward Learning Method Handling Simultaneous Learning Episodes in a Dynamic Environment with Emerging Tasks

抄録

Average reward learning methods (ARLMs) show a poor performance in environments in which they must deal with several tasks simultaneously. In this paper we present the evaluation of an ARLM adapted to handle simultaneous learning episodes. We compare its performance against a conventional ARLM in a multicar elevator system.