Alternatives and similar repositories for monte-carlo-tree-search:

Users that are interested in monte-carlo-tree-search are comparing it to the libraries listed below

• haroldsultan / MCTS
  Python Implementations of Monte Carlo Tree Search
  ☆302Updated 3 years ago
• Shmuma / ptan
  PyTorch Agent Net: reinforcement learning toolkit for pytorch
  ☆545Updated 6 months ago
• pbsinclair42 / MCTS
  A simple package to allow users to run Monte Carlo Tree Search on any perfect information domain
  ☆222Updated 11 months ago
• huangeddie / GymGo
  An environment of the board game Go using OpenAI's Gym API
  ☆172Updated 3 years ago
• dylandjian / SuperGo
  A student implementation of Alpha Go Zero
  ☆280Updated 6 years ago
• MorvanZhou / pytorch-A3C
  Simple A3C implementation with pytorch + multiprocessing
  ☆638Updated 2 years ago
• MattChanTK / gym-maze
  A basic 2D maze environment where an agent start from the top left corner and try to find its way to the bottom left corner.
  ☆366Updated last year
• hildensia / mcts
  An implementation of Monte Carlo Tree Search in python
  ☆162Updated 4 years ago
• google-deepmind / dqn_zoo
  DQN Zoo is a collection of reference implementations of reinforcement learning agents developed at DeepMind based on the Deep Q-Network (…
  ☆472Updated last year
• facebookresearch / torchbeast
  A PyTorch Platform for Distributed RL
  ☆747Updated 3 years ago
• initial-h / AlphaZero_Gomoku_MPI
  An asynchronous/parallel method of AlphaGo Zero algorithm with Gomoku
  ☆206Updated 2 months ago
• oxwhirl / smac
  SMAC: The StarCraft Multi-Agent Challenge
  ☆1,197Updated last year
• koulanurag / muzero-pytorch
  Pytorch Implementation of MuZero
  ☆352Updated last year
• koulanurag / ma-gym
  A collection of multi agent environments based on OpenAI gym.
  ☆597Updated 10 months ago
• uber-research / go-explore
  Code for Go-Explore: a New Approach for Hard-Exploration Problems
  ☆566Updated 2 years ago
• rail-berkeley / softlearning
  Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official imp…
  ☆1,294Updated last year
• lcswillems / rl-starter-files
  RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code
  ☆684Updated 11 months ago
• haarnoja / sac
  Soft Actor-Critic
  ☆1,086Updated last year
• sjtu-marl / malib
  A parallel framework for population-based multi-agent reinforcement learning.
  ☆528Updated last year
• google-research / batch_rl
  Offline Reinforcement Learning (aka Batch Reinforcement Learning) on Atari 2600 games
  ☆546Updated last year
• haarnoja / softqlearning
  Reinforcement Learning with Deep Energy-Based Policies
  ☆422Updated last year
• david-abel / simple_rl
  A simple framework for experimenting with Reinforcement Learning in Python.
  ☆311Updated last year
• sfujim / BCQ
  Author's PyTorch implementation of BCQ for continuous and discrete actions
  ☆627Updated 4 years ago
• openai / gym-soccer
  ☆303Updated 2 years ago
• Farama-Foundation / Minigrid
  Simple and easily configurable grid world environments for reinforcement learning
  ☆2,231Updated 3 months ago
• jannerm / mbpo
  Code for the paper "When to Trust Your Model: Model-Based Policy Optimization"
  ☆489Updated 2 years ago
• zhangchuheng123 / Reinforcement-Implementation
  Implementation of benchmark RL algorithms
  ☆466Updated 2 years ago
• mpSchrader / gym-sokoban
  Sokoban environment for OpenAI Gym
  ☆360Updated last year
• MrSyee / pg-is-all-you-need
  Policy Gradient is all you need! A step-by-step tutorial for well-known PG methods.
  ☆917Updated 3 weeks ago
• qfettes / DeepRL-Tutorials
  Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
  ☆1,070Updated 3 years ago