Title: Talk, Judge, Cooperate: Gossip-Driven Indirect Reciprocity in Self-Interested LLM Agents
Primary area: alignment, fairness, safety, privacy, and societal considerations
Keywords: Indirect Reciprocity, LLM Agent, Game Theory, Gossip, Reputation, Cooperation, Multi-agent System

Abstract: Decentralized self-interested LLM agents often struggle to sustain cooperation when they are placed in mixed-motive tasks. Incentivizing cooperation is challenging while many previous studies have focused on compromised settings. We address this challenge by introducing public gossip as a decentralized reputation mechanism in agents' interactions. Our analysis provides both theoretical guarantees and empirical evidence that gossip can promote cooperation in indirect reciprocity games. Building on this insight, we propose the Agentic LInguistic Gossip Network (ALIGN), an automated agentic framework where agents share open-ended gossip to evaluate one another's trustworthiness and establish reciprocity with cooperative partners. Experiments show that ALIGN not only improves cooperation and social welfare but also resists malicious entrants, as defectors are reliably identified and excluded.