Evaluating LLMs in Open-Source Games
Swadesh Sistla, Max Kleiman-Weiner
The emergence of programming and strategic reasoning abilities in large language models (LLMs) enable their participation in \textit{program meta-games}: a game-theoretic setting in which players submit computer programs in lieu of moves. These programs offer various possible advantages, including human interpretability, local transparency, and formal verifiability; additionally, they enable \textit{program equilibria}, solution concepts reliant upon program submission and inaccessible within normal form settings. We evaluate the capabilities of leading open-source and closed-weight LLMs to behaviorally predict and classify program meta-game strategies, implement program equilibrium solution concepts, and play program meta-games against other LLM agents across dyadic and evolutionary settings. We identify the emergence of payoff-maximizing, cooperative, and deceptive strategies, as well as LLM-based implementations of existing program equilibrium solution concepts.