Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
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Updated
May 6, 2024 - Jupyter Notebook
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
An elegant PyTorch deep reinforcement learning library.
ELF: a platform for game research with AlphaGoZero/AlphaZero reimplementation
An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning
A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
Refer to https://github.com/AcutronicRobotics/gym-gazebo2 for the new version
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
Python library for Reinforcement Learning.
[NeurIPS'21 Outstanding Paper] Library for reliable evaluation on RL and ML benchmarks, even with only a handful of seeds.
Hearthstone simulator using C++ with some reinforcement learning
A curated list of Monte Carlo tree search papers with implementations.
Implementation of papers in 100 lines of code.
Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019
📘 The MLOps stack component for experiment tracking
Implementation of Inverse Reinforcement Learning (IRL) algorithms in Python/Tensorflow. Deep MaxEnt, MaxEnt, LPIRL
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