Host: The Society of Instrument and Control Engineers
Co-host: IEEE/Industiral Electronic Society, IEEE/Robotics and Automation Society, IEEE/Control System Society
Pages 62
The main problem of reinforcement learning is that learning converges slowly. As one of the solution, McGovern proposed “macro-action”. However, a human expert needs to design macro-actions which adapt to an environment. In this paper, we propose a new method that enables to generate the macro-actions which adapt to the enviroment automatically using genetic algorithm.