Akihiko Yamaguchi

Neural networks and differential dynamic programming for reinforcement learning problems

We explore a model-based approach to reinforcement learning where partially or totally unknown dynamics are learned and explicit planning is performed. We learn dynamics with neural networks, and plan behaviors with differential dynamic programming (DDP). In order to handle complicated dynamics, suc