Blockwise Sequential Model Learning for Partially Observable Reinforcement Learning

Giseung Park, Sungho Choi, Youngchul Sung

This paper proposes a new sequential model learning architecture to solve partially observable Markov decision problems. Rather than compressing sequential information at every tim…