Basic dataset creation, embedding learning, and evaluation tasks on Kuhn and Leduc Poker demonstrate that useful behavioral representations appear in the learned embeddings.
Con- trastive learning-based agent modeling for deep reinforcement learning.arXiv preprint arXiv:2401.00132, 2024
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Towards Learning Representations of Policies in Two-Player Zero-Sum Imperfect-Information Games
Basic dataset creation, embedding learning, and evaluation tasks on Kuhn and Leduc Poker demonstrate that useful behavioral representations appear in the learned embeddings.