Model-based Reinforcement Learning with a Hamiltonian Canonical ODE Network

Yao Feng, Yuhong Jiang, Hang Su +2

Model-based reinforcement learning usually suffers from a high sample complexity in training the world model, especially for the environments with complex dynamics. To make the tra…