ma-gym VS GoBigger

Compare ma-gym vs GoBigger and see what are their differences.

ma-gym

A collection of multi agent environments based on OpenAI gym. (by koulanurag)

GoBigger

[ICLR 2023] Come & try Decision-Intelligence version of "Agar"! Gobigger could also help you with multi-agent decision intelligence study. (by opendilab)
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ma-gym GoBigger
2 1
581 463
- 0.0%
3.9 3.2
6 months ago over 1 year ago
Python Python
Apache License 2.0 Apache License 2.0
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.

ma-gym

Posts with mentions or reviews of ma-gym. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-05-06.

GoBigger

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

What are some alternatives?

When comparing ma-gym and GoBigger you can also consider the following projects:

mcts-general - General Python implementation of Monte Carlo Tree Search for the use with Open AI Gym environments.

Gym-Trading-Env - A simple, easy, customizable Gymnasium environment for trading.

Minigrid - Simple and easily configurable grid world environments for reinforcement learning

lol-account-manager - account manager

crafter - Benchmarking the Spectrum of Agent Capabilities

stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

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

skill-expression-game-analysis - Finding a method to objectively quantify skill expression in games, using reinforcement learning

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