Tsuyoshi SUZUKI

Policy Selection Method based on Spreading Activation Model for Reinforcement Learning Agent

2017 · The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)

This paper proposes a policy selection method of a reinforcement learning agent for suitable learning in unknown or dynamic environments based on a spreading activation model in the cognitive psychology. The reinforcement learning agent saves …