rlalgorithms-tf2
TensorLayer
| rlalgorithms-tf2 | TensorLayer | |
|---|---|---|
| 18 | 1 | |
| 45 | 7,275 | |
| - | 0.0% | |
| 4.7 | 0.0 | |
| almost 2 years ago | about 1 year ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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rlalgorithms-tf2
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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.
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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
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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
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xagents: deep reinforcement learning command line tool box
Project page
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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
TensorLayer
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Introduction to ‘TensorLayer’: A Python-based Versatile Deep Learning Library Designed for Machine Learning Researchers
Github: https://github.com/tensorlayer/TensorLayer
What are some alternatives?
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
nngen - NNgen: A Fully-Customizable Hardware Synthesis Compiler for Deep Neural Network
IRL - Algorithms for Inverse Reinforcement Learning
chainerrl - ChainerRL is a deep reinforcement learning library built on top of Chainer.
DeepRL-TensorFlow2 - 🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
gpt-j-chatbot - A GPT-J Chatbot Template for creating AI Characters (Virtual Girlfriend Chatbot, Replika-esque)
tf2multiagentrl - Clean implementation of Multi-Agent Reinforcement Learning methods (MADDPG, MATD3, MASAC, MAD4PG) in TensorFlow 2.x
yagooglesearch - Yet another googlesearch - A Python library for executing intelligent, realistic-looking, and tunable Google searches.
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.
SRGAN - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
agents - TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
biprop - Identify a binary weight or binary weight and activation subnetwork within a randomly initialized network by only pruning and binarizing the network.