Mava
tf2multiagentrl
Our great sponsors
| Mava | tf2multiagentrl | |
|---|---|---|
| 5 | - | |
| 645 | 110 | |
| 5.7% | - | |
| 9.9 | 3.4 | |
| 9 days ago | 6 months ago | |
| Python | Python | |
| 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
-
Starting wth Multi Agent Reinforcement Learning
If you want to play with models and algorithms around MARL, take a look at Mava.
-
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).
-
Training with multiple agents.
The OpenSpiel games (as well as several others) are also available from MAVA (https://github.com/instadeepai/Mava).
-
[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
tf2multiagentrl
We haven't tracked posts mentioning tf2multiagentrl yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
acme - A library of reinforcement learning components and agents
DeepRL-TensorFlow2 - 🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
lingvo - Lingvo
rlalgorithms-tf2 - Packaged deep reinforcement learning algorithms in tensorflow 2.x
pymarl2 - Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)
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).
PettingZoo - An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
multi_agent_path_planning - Python implementation of a bunch of multi-robot path-planning algorithms.
agents-aea - A framework for autonomous economic agent (AEA) development
IC3Net - Code for ICLR 2019 paper: Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.