1A1-F10 異種センサ統合のためのニューラルネットワーク型強化学習(進化・学習とロボティクス(1))

抄録

This paper proposes a new reinforcement learning algorithm which can learn in the multi-dimensional input spaces containing different-species sensors by means of CMAC and neural networks. We apply the proposed method to a robot arm reaching problem and verify the effectivity of the proposed method.