Origen AI

Automatic Critical Mechanic Discovery Using Playtraces in Video Games

Automated identification of critical game mechanics—the essential actions required to achieve victory—represents a significant advancement in computational game analysis.

• Automated identification of critical game mechanics by combining game description parsing with empirical playtraces more accurately reflects human-identified priorities than baseline methods like AtDelfi.
• Integrating discovered critical mechanics into Monte Carlo Tree Search agents significantly improves win rates in complex game environments such as Plants.
• Prioritizing critical actions within an agent's decision-making framework increases the efficiency and goal-orientation of the planning process.

Mech-Elites: Illuminating the Mechanic Space of GVG-AI

Mech-Elites serves as a framework for automating the design of tutorial levels within the General Video Game Artificial Intelligence (GVG-AI) environment.