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LLM agents in Mafia game show communication's complex role in collective inference

By PulseAugur Editorial · [1 sources] ·

Researchers explored how communication strategies impact collective inference in self-adapting societies of large language models, using the game of Mafia as a testbed. The study found that simultaneous broadcast communication improved adversary identification compared to silence across various group sizes and compositions. However, this advantage diminished with larger groups and over time as agents adapted their strategies, sometimes leading to worse performance than silent groups. The adaptation process, driven by agents rewriting and inheriting strategy notes, showed that communication's value is intertwined with the evolving signals it generates. AI

IMPACT Demonstrates how communication protocols and agent adaptation influence collective decision-making in LLM societies.

RANK_REASON Academic paper detailing a simulation study on LLM agent behavior. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLM agents in Mafia game show communication's complex role in collective inference

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Academic paper detailing a simulation study on LLM agent behavior. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Joey Xiao ·

    Communication Shapes Collective Inference in Self-Adapting LLM Societies: Evidence from Mafia

    When does communication help a group identify hidden adversaries, and how does its value change as the group adapts? In Mafia, an informed minority hides inside an uninformed majority whose only evidence is open play. The zero-information game, where each day's vote eliminates a …

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