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cs.MA2026
Risk-seeking conservative policy iteration with agent-state based policies for Dec-POMDPs with guaranteed convergence
Amit Sinha, Matthieu Geist, Aditya Mahajan
Optimally solving decentralized decision-making problems modeled as Dec-POMDPs is known to be NEXP-complete. These optimal solutions are policies based on the entire history of obs…
cs.LG2026
Multi-agent imitation learning with function approximation: Linear Markov games and beyond
Luca Viano, Till Freihaut, Emanuele Nevali +3
In this work, we present the first theoretical analysis of multi-agent imitation learning (MAIL) in linear Markov games where both the transition dynamics and each agent's reward f…