policy-adaptation-during-deployment
envpool
| policy-adaptation-during-deployment | envpool | |
|---|---|---|
| 1 | 3 | |
| 109 | 1,017 | |
| - | 1.8% | |
| 1.8 | 4.2 | |
| over 3 years ago | about 1 month ago | |
| Python | C++ | |
| - | 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.
policy-adaptation-during-deployment
-
Exploring Self-Supervised Policy Adaptation To Continue Training After Deployment Without Using Any Rewards
Code: https://github.com/nicklashansen/policy-adaptation-during-deployment
envpool
-
How do I improve my SB3 PPO on an EnvPool environment
I am looking to improve the overall performance as well as optimize the wall clock time. I slightly modified the code to develop a SB3 wrapper for envpool from here.
-
[D] Adding a new RL environment to envpool
Envpool provides high parallelization of RL environments. Unfortunately, there are still many environments that are not supported by them. One of them is FrankaKitchen of D4RL, a library for offline RL.
-
[R] EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine
Code for https://arxiv.org/abs/2206.10558 found: https://github.com/sail-sg/envpool
What are some alternatives?
Ne2Ne-Image-Denoising - Deep Unsupervised Image Denoising, based on Neighbour2Neighbour training
ns3-gym - ns3-gym - The Playground for Reinforcement Learning in Networking Research
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
thread-pool - BS::thread_pool: a fast, lightweight, and easy-to-use C++17 thread pool library
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).
matplotlibcpp17 - Alternative to matplotlibcpp with better syntax, based on pybind
drl_grasping - Deep Reinforcement Learning for Robotic Grasping from Octrees
ecole - Extensible Combinatorial Optimization Learning Environments
dmc2gymnasium - Gymnasium integration for the DeepMind Control (DMC) suite
Taskflow - A General-purpose Parallel and Heterogeneous Task Programming System
es_pytorch - High performance implementation of Deep neuroevolution in pytorch using mpi4py. Intended for use on HPC clusters
pyTORCS-docker - Docker-based, gym-like torcs environment with vision.