Autoformalization of Game Descriptions using Large Language Models

Understand

Game theory is a powerful framework for reasoning about strategic interactions, with applications in domains ranging from day-to-day life to international politics.

• However, applying formal reasoning tools in such contexts is challenging, as these scenarios are often expressed in natural language.
• To address this, we introduce a framework for the autoformalization of game-theoretic scenarios, which translates natural language descriptions into formal logic representations suitable for formal solvers.
• Our approach utilizes one-shot prompting and a solver that provides feedback on syntactic correctness to allow LLMs to refine the code.