Approximating Human Strategic Reasoning with LLM-Enhanced Recursive Reasoners Leveraging Multi-agent Hypergames

• URL: http://arxiv.org/abs/2502.07443v1
• Date: Tue, 11 Feb 2025 10:37:20 GMT
• Title: Approximating Human Strategic Reasoning with LLM-Enhanced Recursive Reasoners Leveraging Multi-agent Hypergames
• Authors: Vince Trencsenyi, Agnieszka Mensfelt, Kostas Stathis,
• Abstract summary: We implement a role-based multi-agent strategic interaction framework tailored to sophisticated reasoners.<n>We use one-shot, 2-player beauty contests to evaluate the reasoning capabilities of the latest LLMs.<n>Our experiments show that artificial reasoners can outperform the baseline model in terms of both approximating human behaviour and reaching the optimal solution.
• Score: 3.5083201638203154
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: LLM-driven multi-agent-based simulations have been gaining traction with applications in game-theoretic and social simulations. While most implementations seek to exploit or evaluate LLM-agentic reasoning, they often do so with a weak notion of agency and simplified architectures. We implement a role-based multi-agent strategic interaction framework tailored to sophisticated recursive reasoners, providing the means for systematic in-depth development and evaluation of strategic reasoning. Our game environment is governed by the umpire responsible for facilitating games, from matchmaking through move validation to environment management. Players incorporate state-of-the-art LLMs in their decision mechanism, relying on a formal hypergame-based model of hierarchical beliefs. We use one-shot, 2-player beauty contests to evaluate the recursive reasoning capabilities of the latest LLMs, providing a comparison to an established baseline model from economics and data from human experiments. Furthermore, we introduce the foundations of an alternative semantic measure of reasoning to the k-level theory. Our experiments show that artificial reasoners can outperform the baseline model in terms of both approximating human behaviour and reaching the optimal solution.

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