Pessimism-Free Offline Learning in General-Sum Games via KL Regularization
arXiv:2605.00264v1 Announce Type: new
Abstract: Offline multi-agent reinforcement learning in general-sum settings is challenged by the distribution shift between logged datasets and target equilibrium policies. While standard methods rely on manual p…