Reinforcement learning for continuous state spaces based on locally weighted regression

Abstract

On reinforcement learning researches, even though environments have continuous state space, many RL algorithms are assumed to be on a discrete state space. Typically, most approaches which treat continuous state and action spaces, just discretise these spaces. In this paper, to treat the continuous state space, we propose a RL algorithm which based on the locally weighted regression.