Mava
maro
Our great sponsors
| Mava | maro | |
|---|---|---|
| 5 | 9 | |
| 645 | 813 | |
| 5.7% | 2.5% | |
| 9.9 | 3.5 | |
| 4 days ago | about 2 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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
maro
-
Headstart for multi-container optimization problem.
Yes, I have actually. Some of them which i could find out were: https://github.com/tryton/tryton/tree/main https://pypi.org/project/pyShipping-python3/ https://github.com/microsoft/maro https://github.com/yat-co/yat-trailer-loading https://github.com/duyet/openerp-6.1.1
- maro: NEW Deep Learning And Reinforcement Learning - star count:609.0
-
What's the outlook of Reinforcement Learning?
As far as current SOTA applications, you can just Google it and find plenty of examples of RL being used outside the realm of games. Video/board games offer a nice domain for research in RL, but the underlying algorithms can be (and have been) applied to plenty of domains outside of this. A big one, currently, is robotics. Another example is resource optimization, which is probably currently being developed, if not used, in a lot of technical domains. As u/daddabarba pointed out, RL can also be used in other areas of AI, like text generation.
What are some alternatives?
acme - A library of reinforcement learning components and agents
openerp-6.1.1
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).
lingvo - Lingvo
yat-trailer-loading - Temp Repo for Trailer Loading
pymarl2 - Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)
agents-aea - A framework for autonomous economic agent (AEA) development
VMAgent - Our VMAgent is a platform for exploiting Reinforcement Learning (RL) on Virtual Machine (VM) scheduling tasks.
multi_agent_path_planning - Python implementation of a bunch of multi-robot path-planning algorithms.
blender-quadcopter-fpv - Quadcopter FPV Simulator for blender to capture epic footage