Avoiding collaborative paradox in multi‐agent reinforcement learning

H Kim, S Kim, D Lee, I Jang - ETRI Journal, 2021 - Wiley Online Library
The collaboration productively interacting between multi‐agents has become an emerging
issue in real‐world applications. In reinforcement learning, multi‐agent environments …

Learning Invariant Reward Functions through Trajectory Interventions

I Ovinnikov, E Bykovets, JM Buhmann - openreview.net
Inverse reinforcement learning methods aim to retrieve the reward function of a Markov
decision process based on a dataset of expert demonstrations. The commonplace scarcity of …