Emergent-Multiagent-Strategies
DI-engine
| Emergent-Multiagent-Strategies | DI-engine | |
|---|---|---|
| 1 | 3 | |
| 38 | 2,603 | |
| - | 7.5% | |
| 0.0 | 8.7 | |
| over 1 year ago | 7 days ago | |
| Python | Python | |
| MIT License | 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.
Emergent-Multiagent-Strategies
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PPO with Transformer or Attention Mechanism
Not stable_baselines but I have an implementation of Attention + PPO in a multi-agent setting: https://github.com/Ankur-Deka/Emergent-Multiagent-Strategies
DI-engine
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Anyone have experience with DI-Engine?
I posted a while back asking people what frameworks they were using for RL research. Recently i stumbled upon DI-Engine which looks promising! Actively maintained, with a diverse set of algorithms already implemented.
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TransformerXL + PPO Baseline + MemoryGym
DI Engine
- Struggling with algorithm generality? Try DI engine; here is the solution
What are some alternatives?
IC3Net - Code for ICLR 2019 paper: Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks
stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
Competitive-Programming
pytorch-a2c-ppo-acktr-gail - PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
pumpkin - The MAS Demonic Surveillance Platform. 🎃 [Moved to: https://github.com/scandale-project/pumpkin]
tianshou - An elegant PyTorch deep reinforcement learning library.
pymarl2 - Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)
seed_rl - SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
Mava - 🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
on-policy - This is the official implementation of Multi-Agent PPO (MAPPO).
myosuite - MyoSuite is a collection of environments/tasks to be solved by musculoskeletal models simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API.