Arxiv paper - Strategic Intelligence in Large Language Models: Evidence from evolutionary Game Theory

In this episode, we discuss Strategic Intelligence in Large Language Models: Evidence from evolutionary Game Theory by Kenneth Payne, Baptiste Alloui-Cros. The paper investigates whether Large Language Models (LLMs) can engage in strategic decision-making by testing them in evolutionary Iterated Prisoner’s Dilemma tournaments against classic strategies. Results show that LLMs are highly competitive and exhibit distinct strategic behaviors, with different models displaying varying levels of cooperation and retaliation. The authors further analyze the models’ reasoning processes, revealing that LLMs actively consider future interactions and opponent strategies, bridging game theory with machine psychology.