Yinan Wang

Self-Supervised Reinforcement Learning for Out-of-Distribution Recovery via Auxiliary Reward

Recently, the real-world applications of reinforcement learning (RL) have seen the problem of taking actions in an out-of-distribution (OOD) state. However, most existing research is limited to take actions to narrow the visited training distribution and OOD, and does not consider the efficiency to…