Towards Unraveling and Improving Generalization in World Models

Qiaoyi Fang, Weiyu Du, Hang Wang +1

World models have recently emerged as a promising approach to reinforcement learning (RL), achieving state-of-the-art performance across a wide range of visual control tasks. This…