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2024

Evolution of Social Norms in LLM Agents using Natural Language

Horiguchi, Ilya, Yoshida, Takahide, Ikegami, Takashi

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Recent advancements in Large Language Models (LLMs) have spurred a surge of interest in leveraging these models for game-theoretical simulations, where LLMs act as individual agents engaging in social interactions.

This study explores the potential for LLM agents to spontaneously generate and adhere to normative strategies through natural language discourse, building upon the foundational work of Axelrod's metanorm games.
Our experiments demonstrate that through dialogue, LLM agents can form complex social norms, such as metanorms-norms enforcing the punishment of those who do not punish cheating-purely through natural language interaction.
The results affirm the effectiveness of using LLM agents for simulating social interactions and understanding the emergence and evolution of complex strategies and norms through natural language.

Evolution of Social Norms in LLM Agents using Natural Language · Around

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An evolutionary approach to norms
Axelrod, R. (1986) · 1986
Earlier work this paper cites.
The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration
Axelrod, R. (1998) · 1998
Earlier work this paper cites.
Axelrod’s metanorm games on networks
Galán, J. M., Łatek, M. M., and Rizi, S. M. M. (2011) · 2011
Earlier work this paper cites.

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