Presentation information

General Session

General Session » [GS] J-2 Machine learning

[1I3-J-2] Machine learning: advances in reinforcement learning

Tue. Jun 4, 2019 3:20 PM - 4:20 PM Room I (306+307 Small meeting rooms)

3:20 PM - 3:40 PM

[1I3-J-2-01] Development of Optimal Control Using AlphaZero Reinforcement Learning Algorithm

〇Watabe Masaya1, Kun Yang1, Dinesh Malla2, Katsuyoshi Sakamoto1, Kouichi Yamguchi1, Tomah Sogabe1,3 (1. The University of Electro-Communications, 2. Grid Inc., 3. i-PERC, The University of Electro-Communications)

Keywords:AlphaZero, Reinforcement learning, Optimal control

Deep Learning and Reinforcement Learning are developing rapidly in recent years. A lot of researches which apply deep reinforcement learning to the field such as game and robot control have generated great success. In this paper, we examine the possibility of adopting AlphaZero, an reinforcement learning algorithm demonstrates an unprecedented level of versatility for an game AI, to optimal control problems and gain insight on its ability to control the actions under noisy environment that is difficult to handle by using conventional control mechanism.