This research examines how systems of LLM agents behave when faced with strategic social dilemmas, particularly focusing on their capacity for cooperation.

• LLMs were prompted to generate complete strategies for iterated Prisoner's Dilemma scenarios
• Researchers used evolutionary game theory to simulate populations with different strategic tendencies
• Results reveal insights about how autonomous AI systems might cooperate or compete without explicit programming
• Findings have profound implications for multi-agent AI systems in gaming environments

For gaming applications, this research helps predict how autonomous agents might interact in competitive or collaborative scenarios, informing more realistic game dynamics and AI behavior systems.

Will Systems of LLM Agents Cooperate: An Investigation into a Social Dilemma