Cooperation Without Adaptation: LLM Agents in a Collective-Risk Dilemma
Language-model agents are increasingly deployed to act on behalf of people in settings where individual decisions shape shared outcomes.
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Key points
- We examine whether five production models adapt their contributions to changing risks and partner behaviour, or instead follow a relatively fixed strategy.
- In a collective-risk dilemma game (CRG), six players contribute to a shared pool over ten rounds; if the pool falls short of its target, a catastrophe may destroy their remaining resources.
- Payoff-based selection also depended on population composition: in a single six-agent group, it favoured the model that contributed least and reduced group success, whereas in larger, randomly mixed populations, it favoured an exact fair-share model at moderate and high risk.
- These findings show that cooperative self-play alone is not evidence of strategic adaptability.
Sources (1)
- [1]Cooperation Without Adaptation: LLM Agents in a Collective-Risk DilemmaarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 16, 03:38 AM
Language-model agents are increasingly deployed to act on behalf of people in settings where individual decisions shape shared outcomes.
We examine whether five production models adapt their contributions to changing risks and partner behaviour, or instead follow a relatively fixed strategy.
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