CollabSim is a new CSCW-grounded simulation framework that enables controlled multi-agent experiments to measure collaborative competence in LLM agents.
CoopEval: Benchmarking Cooperation-Sustaining Mechanisms and LLM Agents in Social Dilemmas
3 Pith papers cite this work. Polarity classification is still indexing.
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abstract
It is increasingly important that LLM agents interact effectively and safely with other goal-pursuing agents, yet, recent works report the opposite trend: LLMs with stronger reasoning capabilities behave _less_ cooperatively in mixed-motive games such as the prisoner's dilemma and public goods settings. Indeed, our experiments show that recent models -- with or without reasoning enabled -- consistently defect in single-shot social dilemmas. To tackle this safety concern, we present the first comparative study of game-theoretic mechanisms that are designed to enable cooperative outcomes between rational agents _in equilibrium_. Across four social dilemmas testing distinct components of robust cooperation, we evaluate the following mechanisms: (1) repeating the game for many rounds, (2) reputation systems, (3) third-party mediators to delegate decision making to, and (4) contract agreements for outcome-conditional payments between players. Among our findings, we establish that contracting and mediation are most effective in achieving cooperative outcomes between capable LLM models, and that repetition-induced cooperation deteriorates drastically when co-players vary. Moreover, we demonstrate that these cooperation mechanisms become _more effective_ under evolutionary pressures to maximize individual payoffs.
years
2026 3representative citing papers
A folk theorem for LLM guides: any feasible, individually rational payoff vector can be sustained as an ε-equilibrium despite unobservable, unattributable deviations.
Group selection on transmitted prompts in LLM agent populations promotes and stabilizes cooperation in social dilemmas while individual selection produces collective defection.
citing papers explorer
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CollabSim: A CSCW-Grounded Methodology for Investigating Collaborative Competence of LLM Agents through Controlled Multi-Agent Experiments
CollabSim is a new CSCW-grounded simulation framework that enables controlled multi-agent experiments to measure collaborative competence in LLM agents.
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Who Is Really Playing? Strategic Interaction in AI-Guided Populations
A folk theorem for LLM guides: any feasible, individually rational payoff vector can be sustained as an ε-equilibrium despite unobservable, unattributable deviations.
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Group Selection Promotes Prosocial Prompts in Populations of LLM Agents
Group selection on transmitted prompts in LLM agent populations promotes and stabilizes cooperation in social dilemmas while individual selection produces collective defection.