Author

Tomáš Holeček

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#machine learning Preprint Sep 2026

NashDreamer: Model-Based Reinforcement Learning for Zero-Sum Imperfect-Information Games

NashDreamer is proposed, a principled MBRL framework for two-player zero-sum IIGs that introduces a centralized Multi-Agent Recurrent State-Space Model (MARSSM) that decouples environment dynamics from the effect of players's strategies on their individual observations.

Tomáš Holeček, Viliam Lisý · 0 citations