Our paper was accepted for ICLR2021.
Our paper was accepted for presentation at ICLR2021. 【Information】Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, and Shixiang Shane Gu. “Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization”, International Conference on Learning Representations 2021 (ICLR2021). May 2021. 【Overview】Most reinforcement learning (RL) algorithms assume online access to the environment, in which one may readily interleave updates to…