Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization

Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo +2

Most reinforcement learning (RL) algorithms assume online access to the environment, in which one may readily interleave updates to the policy with experience collection using that…