Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient

Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang

Abstract: This paper provides a statistical analysis of high-dimensional batch reinforcement learning (RL) using sparse linear function approximation. When there is a large number of candidate features, our ...