UlisseMini/procgen-tools
Tools for running experiments on RL agents in procgen environments
This project provides specialized tools for analyzing and understanding how reinforcement learning agents behave within the 'maze' environment of the Procgen benchmark. It allows researchers to input trained agent models and maze configurations, then observe and manipulate the agent's internal decision-making processes and resulting actions. This is primarily for AI/ML researchers studying agent interpretability, goal misgeneralization, and behavioral statistics in controlled environments.
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Use this if you are an AI/ML researcher investigating the internal workings of reinforcement learning agents, specifically their decision-making in maze-like environments, and want to test hypotheses about their goal-directed behavior.
Not ideal if you are looking for a stable, production-ready library with extensive documentation or if your research involves environments other than the Procgen 'maze' or different types of AI models.
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Jupyter Notebook
License
MIT
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Last pushed
Apr 05, 2024
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