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cs.LG2025
Distributional Inverse Reinforcement Learning
Feiyang Wu, Ye Zhao, Anqi Wu
We propose a distributional framework for offline Inverse Reinforcement Learning (IRL) that jointly models uncertainty over reward functions and full distributions of returns. Unli…
cs.LG2025
Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors
Jingyang Ke, Feiyang Wu, Jiyi Wang +2
Traditional approaches to studying decision-making in neuroscience focus on simplified behavioral tasks where animals perform repetitive, stereotyped actions to receive explicit re…