AI RESEARCH
Constraint Learning in Multi-Agent Dynamic Games from Demonstrations of Local Nash Interactions
arXiv CS.LG
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ArXi:2508.19945v4 Announce Type: replace We present an inverse dynamic game-based algorithm to learn parametric constraints from a given dataset of local Nash equilibrium interactions between multiple agents. Specifically, we