ACE VS pymarl2

Compare ACE vs pymarl2 and see what are their differences.

ACE

[AAAI 2023] Official PyTorch implementation of paper "ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency". (by opendilab)
gfootball multi-agent multi-agent-reinforcement-learning reinforcement-learning smac
Source Code
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pymarl2

Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios) (by hijkzzz)
marl smac starcraft sota reinforcement-learning
Source Code
iclr-blogposts.github.io
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ACE pymarl2
1 1
186 557
0.0% -
10.0 5.0
over 1 year ago 4 months 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.

ACE

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

pymarl2

Posts with mentions or reviews of pymarl2. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-17.

What are some alternatives?

When comparing ACE and pymarl2 you can also consider the following projects:

chatarena - ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

nlp-recipes - Natural Language Processing Best Practices & Examples

Mava - 🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX

auto-sklearn - Automated Machine Learning with scikit-learn

ai-economist - Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).

fast-reid - SOTA Re-identification Methods and Toolbox

SimpleView - Official Code for ICML 2021 paper "Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline"

Emergent-Multiagent-Strategies - Emergence of complex strategies through multiagent competition

ACE vs chatarena pymarl2 vs nlp-recipes ACE vs Mava pymarl2 vs auto-sklearn pymarl2 vs ai-economist pymarl2 vs Mava pymarl2 vs fast-reid pymarl2 vs SimpleView pymarl2 vs Emergent-Multiagent-Strategies