Do LLMs Take Care of Their Own? Similarity Signals Can Induce Cooperation
As LLM-based agents with user-instructed goals are becoming widely deployed, they increasingly encounter each other in strategic interactions, and face challenges of finding mutually beneficial outcomes. Prior literature has argued that cooperation problems such as the Prisoner's Dilemma are resolvable in settings where agents know they follow very similar decision making patterns, as for example in monocultural AI ecosystems. Following that line of work, this paper introduces the first framework for evaluating LLM decision making when agents are provided with graded similarity signals. Among our findings, we establish that different LLM models vary drastically in how they navigate simila...
| Authors | Akash Kundu, Emanuel Tewolde, Ratip Emin Berker et al. |
|---|---|
| Primary category | cs.GT |
| Published | 12 August 2026 |
| Last updated at source | 12 August 2026 |
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