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)
DI-engine docs (Chinese and English)
PyTorch implementation of Hierarchical Actor Critic (HAC) for OpenAI gym environments
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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