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This work formalizes the interaction between AI systems and users as a game with three players: a defender and an attacker that are computationally or informationally bounded, and an AI that provides public advice and is less constrained.
This paper introduces the first framework for evaluating LLM decision making when agents are provided with graded similarity signals, and develops an LLM-behavioral-game-theoretic model that captures some of their reasoning rationale, and can support cooperative outcomes in equilibrium under sufficiently high similarit...
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