Simple-MADRL-Chess VS PantheonRL

Compare Simple-MADRL-Chess vs PantheonRL and see what are their differences.

Simple-MADRL-Chess

MADRL project solving chess environment using PPO with two different methods: 2 agents/networks and a single agent/network. (by mhyrzt)

PantheonRL

PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more. (by Stanford-ILIAD)
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Simple-MADRL-Chess PantheonRL
1 2
10 117
- 2.6%
7.2 5.0
about 1 year ago 6 months ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Simple-MADRL-Chess

Posts with mentions or reviews of Simple-MADRL-Chess. We have used some of these posts to build our list of alternatives and similar projects.

PantheonRL

Posts with mentions or reviews of PantheonRL. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-02.

What are some alternatives?

When comparing Simple-MADRL-Chess and PantheonRL you can also consider the following projects:

warp-drive - Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)

tianshou - An elegant PyTorch deep reinforcement learning library.

PPO-PyTorch - Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

R-NaD - Experimentation with Regularized Nash Dynamics on a GPU accelerated game

Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros

cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

chesscog - Determining chess game state from an image.

minimalRL - Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

machin - Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...

pytorch-a2c-ppo-acktr-gail - PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).