Repo for the Deep Reinforcement Learning Nanodegree program
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Updated
Nov 16, 2023 - Jupyter Notebook
Repo for the Deep Reinforcement Learning Nanodegree program
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.
A pytorch implementation of MADDPG (multi-agent deep deterministic policy gradient)
Reinforced Recommendation toolkit built around pytorch 1.7
PyTorch C++ Reinforcement Learning
DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)
PyTorch implementation of Hierarchical Actor Critic (HAC) for OpenAI gym environments
DI-engine docs (Chinese and English)
Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]
Train an RL agent to execute natural language instructions in a 3D Environment (PyTorch)
Train an RL agent to localize actively (PyTorch)
A high-performance Atari A3C agent in 180 lines of PyTorch
A pytorch based Gomoku game model. Alpha Zero algorithm based reinforcement Learning and Monte Carlo Tree Search model.
Pytorch solutions for UC Berkeley's cs285 assignments
A repository for implementation of deep reinforcement learning lectured at Samsung
Implementation of Algorithms from the Policy Gradient Family. Currently includes: A2C, A3C, DDPG, TD3, SAC
A PyTorch Implementation of "Optimization of Molecules via Deep Reinforcement Learning".
Pytorch starter code for UC Berkeley's cs285 assignments
Implementation of Multi-Agent Reinforcement Learning algorithm(s). Currently includes: MADDPG
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