Alternatives and similar repositories for RL_Codes:

Users that are interested in RL_Codes are comparing it to the libraries listed below

• msinto93 / DDPG
  Tensorflow implementation of a Deep Deterministic Policy Gradient (DDPG) network, trained on OpenAI Gym environments.
  ☆22Updated 6 years ago
• namidairo777 / Distributed-MADDPG
  Distributed Multi-Agent Cooperation Algorithm based on MADDPG with prioritized batch data.
  ☆101Updated 4 years ago
• HengerLi / SPT-MTD
  ☆9Updated 3 years ago
• gouxiangchen / dueling-DQN-pytorch
  very easy implementation of dueling DQN in pytorch
  ☆71Updated 2 years ago
• Remtasya / Distributional-Multi-Agent-Actor-Critic-Reinforcement-Learning-MADDPG-Tennis-Environment
  The state-of-the-art in multi-agent Reinforcement Learning is the MADDPG algorithm which utilises DDPG actor-critic neural networks where…
  ☆26Updated 5 years ago
• philtabor / Actor-Critic-Methods-Paper-To-Code
  ☆182Updated 3 years ago
• vaibkumr / JobSchedulingRLenv
  Reinforcement learning environment for job scheduling written in python.
  ☆24Updated 5 years ago
• zhouker94 / Multi-Agent-DRL
  Multiagent deep reinforcement learning research project
  ☆27Updated 8 months ago
• cyoon1729 / Multi-agent-reinforcement-learning
  Implementation of Multi-Agent Reinforcement Learning algorithm(s). Currently includes: MADDPG
  ☆64Updated 5 years ago
• jihoonerd / Deep-Reinforcement-Learning-with-Double-Q-learning
  📖 Paper: Deep Reinforcement Learning with Double Q-learning 🕹️
  ☆49Updated 9 months ago
• mohammadasghari / dqn-multi-agent-rl
  Deep Q-learning (DQN) for Multi-agent Reinforcement Learning (RL)
  ☆330Updated 4 years ago
• wuwuwuxxx / Reinforcement-Learning-An-introduction
  solutions to the examples and exercises
  ☆42Updated 8 years ago
• blavad / marl
  Multi-agent reinforcement learning framework
  ☆31Updated 4 years ago
• abhisheksuran / Reinforcement_Learning
  Deep Reinforcement Learning Algorithms implemented with Tensorflow 2.3
  ☆98Updated 2 years ago
• anita-hu / TF2-RL
  Reinforcement learning algorithms implemented for Tensorflow 2.0+ [DQN, DDPG, AE-DDPG, SAC, PPO, Primal-Dual DDPG]
  ☆305Updated 2 years ago
• kshitija2 / Interactive-Multi-objective-Reinforcement-Learning
  Multi-objective reinforcement learning deals with finding policies for tasks where there are multiple distinct criteria to optimize for. …
  ☆20Updated 6 years ago
• KaiYan289 / RLpapersnote
  ☆42Updated 2 months ago
• verystrongjoe / qmix
  qmix
  ☆22Updated 4 years ago
• sherlockHSY / Reinforcement_learning_with_pytorch
  Implement some algorithms of RL
  ☆45Updated last year
• zouchangjie / RL-Nash-Q-learning
  强化学习中纳什Qlearning 实现矩阵博弈
  ☆29Updated 5 years ago
• hsvgbkhgbv / SQDDPG
  This is a framework for the research on multi-agent reinforcement learning and the implementation of the experiments in the paper titled …
  ☆116Updated 3 months ago
• XinJingHao / PPO-Discrete-Pytorch
  A clean and robust Pytorch implementation of PPO on Discrete action space
  ☆64Updated 8 months ago
• fschur / DDQN-with-PyTorch-for-OpenAI-Gym
  Implementation of Double DQN reinforcement learning for OpenAI Gym environments with PyTorch.
  ☆68Updated 6 months ago
• Stable-Baselines-Team / rl-colab-notebooks
  Colab notebooks part of the documentation of Stable Baselines reinforcement learning library
  ☆215Updated last month
• Parsa33033 / Deep-Reinforcement-Learning-DQN
  Deep Reinforcement Learning with DQN, Double DQN, Dueling DQN, Noisy Net (Noisy DQN), and DQN with Prioritized Experience Replay
  ☆95Updated 4 years ago
• axelabels / DynMORL
  Code for Dynamic Weights in Multi-Objective Deep Reinforcement Learning
  ☆91Updated last year
• cts198859 / deeprl_network
  multi-agent deep reinforcement learning for networked system control.
  ☆402Updated 4 years ago
• saashanair / rl-series
  ☆23Updated 2 years ago
• sh2439 / RL-Coursera
  Implementations of Coursera Reinforcement Learning Specialization
  ☆42Updated 5 years ago
• CanePunma / Multi_Agent_Deep_Reinforcement_Learning
  Implement Google Deep Minds DQN for multiple agents for a grid world environment where vehicles must pick up customers.
  ☆27Updated 6 years ago