2026
Mixture-of-World Models: Scaling Multi-Task Reinforcement Learning with Modular Latent Dynamics
ICLR 2026poster
A fundamental challenge in multi-task reinforcement learning (MTRL) is achieving sample efficiency in visual domains where tasks exhibit significant heterogeneity in both observations and dynamics. Model-based RL (MBRL) offers a promising path to sample efficiency through world models, but standard…