AINeutralarXiv – CS AI · 7h ago6/10
🧠
Behavior-Invariant Task Representation Learning with Transformer-based World Models for Offline Meta-Reinforcement Learning
Researchers propose a novel offline meta-reinforcement learning framework combining information-theoretic task representation learning with Transformer-based world models to address distribution shifts in sparse-reward environments. The approach extracts behavior-invariant task representations and applies conservative value penalties to prevent model exploitation, demonstrating improved generalization over existing methods.