kyegomez/OpioidRL
OpioidRL is a cutting-edge reinforcement learning (RL) library that simulates drug addiction behaviors within RL agents. Inspired by the addictive properties of drugs like methamphetamine and crack cocaine, OpioidRL offers a unique environment where agents experience reward dependency, high-risk decision-making, and compulsive behaviors — pushing
The library provides specialized OpenAI Gym-compatible environments (Crack-v0, Meth-v0) that model distinct addiction mechanics—tolerance escalation, withdrawal penalties, and relapse probability—all tunable via configuration parameters. It integrates directly with standard RL frameworks like Stable Baselines3, PyTorch, and TensorFlow through a standardized API, enabling seamless experimentation with addiction-induced behavioral patterns across existing training pipelines.
Available on PyPI.
Stars
8
Forks
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Language
Python
License
MIT
Category
Last pushed
Mar 09, 2026
Commits (30d)
0
Dependencies
7
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