From Gameplay Traces to Game Mechanics: Causal Induction with Large Language Models

This research explores the use of Large Language Models (LLMs) for causal induction to reverse-engineer game mechanics from gameplay traces. By analyzing player behavior, the system can infer the underlying rules and dynamics of a game, offering potential applications in game design, AI agent development, and personalized gaming experiences.