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Foundation model agents can achieve stable cooperation in social dilemmas by inferring behavioral similarities, defying classical game theory's expectations of mutual defection.
Sequence models can learn to cooperate in multi-agent settings simply by training against diverse partners, no explicit meta-learning required.
