Mava
pymarl2
Our great sponsors
| Mava | pymarl2 | |
|---|---|---|
| 5 | 1 | |
| 645 | 556 | |
| 5.7% | - | |
| 9.9 | 5.0 | |
| 3 days ago | 4 months ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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.
Mava
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Starting wth Multi Agent Reinforcement Learning
If you want to play with models and algorithms around MARL, take a look at Mava.
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Recomendations of framework/library for MARL
These are the main reasons we built Mava , a library built specifically for MARL. We are also in the process of rewriting it to be simpler to compose MARL components (communication, central training etc), and we are rewriting our codebase in JAX, so really looking forward to improved performance! (Disclaimer, I am one of the people working on Mava).
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Training with multiple agents.
The OpenSpiel games (as well as several others) are also available from MAVA (https://github.com/instadeepai/Mava).
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[R] Mava: a research framework for distributed multi-agent reinforcement learning
https://arxiv.org/abs/2107.01460 Mava, a scalable framework for research in multi-agent reinforcement learning, contains implementation for several multi-agent systems like multi-agent DQN (MADQN), MADDPG, MAPPO, MAD4PG, DIAL, QMIX, and VDN, and integrates well with multi-agent RL environments like PettingZoo, Flatland, OpenSpiel, RoboCup, and SMAC. On GitHub: https://github.com/instadeepai/Mava
pymarl2
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MARL top conference papers are ridiculous
https://github.com/hijkzzz/pymarl2 (RIIT)
What are some alternatives?
acme - A library of reinforcement learning components and agents
nlp-recipes - Natural Language Processing Best Practices & Examples
lingvo - Lingvo
auto-sklearn - Automated Machine Learning with scikit-learn
tf2multiagentrl - Clean implementation of Multi-Agent Reinforcement Learning methods (MADDPG, MATD3, MASAC, MAD4PG) in TensorFlow 2.x
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
multi_agent_path_planning - Python implementation of a bunch of multi-robot path-planning algorithms.
SimpleView - Official Code for ICML 2021 paper "Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline"
PettingZoo - An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
Emergent-Multiagent-Strategies - Emergence of complex strategies through multiagent competition