rlalgorithms-tf2
rlqp
| rlalgorithms-tf2 | rlqp | |
|---|---|---|
| 18 | 4 | |
| 45 | 79 | |
| - | - | |
| 4.7 | 0.0 | |
| almost 2 years ago | over 2 years ago | |
| Python | ||
| 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.
rlalgorithms-tf2
-
I need suggestions to improve my project
Hello everyone, I published my python project a month ago, it's a command line interface for training, tuning and reusing reinforcement learning algorithms in tensorflow 2.x. It's similar to stable-baselines, tf-agents, and not so many others. It seems like it's not getting enough attention despite the README, license, and everything else.
-
My implementations of RL algorithms + demo and tutorial
Hello deep learners, I added a tutorial jupyter notebook, which walks you through the features quickly and easily. I posted here about my project earlier for those who haven't seen it before, it has my reusable implementations of reinforcement learning algorithms available from the command line. I also added the project to pypi, which makes it available through pip install xagents
-
RL command line tool demo + notebook
I created a command line tool for training and tuning and re-using reinforcement learning algorithms. For more info, you can check the project, and if you like you may also try the notebook I just added which walks you through how to use the features simply and quickly.
- Xagents: Deep reinforcement learning command line tool box
-
xagents: deep reinforcement learning command line tool box
Project page
-
Reinforcement learning quick start using OpenAI gym + xagents + Google Colab
xagents: python library based on tensorflow, which I developed, and it provides a command line interface for training and tuning algorithms on various environments.
- Xagents: Deep reinforcement learning Python library
- Autonomous learning command line tool box
- Elegant command line autonomous learning utility in Python
rlqp
-
[R] Accelerating Quadratic Optimization Up to 3x With Reinforcement Learning
Code for https://arxiv.org/abs/2107.10847 found: https://github.com/berkeleyautomation/rlqp
- AI Research Team From Princeton, Berkeley and ETH Zurich Introduce ‘RLQP’ To Accelerate Quadratic Optimization With Deep Reinforcement Learning (RL)
What are some alternatives?
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
machin - Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
IRL - Algorithms for Inverse Reinforcement Learning
DeepRL-TensorFlow2 - 🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
TensorLayer - Deep Learning and Reinforcement Learning Library for Scientists and Engineers
tf2multiagentrl - Clean implementation of Multi-Agent Reinforcement Learning methods (MADDPG, MATD3, MASAC, MAD4PG) in TensorFlow 2.x
DRL-robot-navigation - Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.
agents - TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
loneliless - A Deep-Q Network playing a single player Pong game. Network done in Python (Tensorflow-gpu) with the single player Pong game implemented in C++ (Openframeworks) and both binded with Pybind11.