Top 23 Python reinforcement-learning Projects
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.Project mention: Writing your First Distributed Python Application with Ray (without multiprocessing) | reddit.com/r/Python | 2021-08-23
Here is an older discussion on dask vs ray from the creators of both projects: https://github.com/ray-project/ray/issues/642
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.Project mention: [D] Resources for Understanding The Original Transformer Paper | reddit.com/r/MachineLearning | 2021-09-08
Code for https://arxiv.org/abs/1706.03762 found: https://github.com/tensorflow/tensor2tensor
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StarCraft II Learning EnvironmentProject mention: Tips for a beginner | reddit.com/r/sc2ai | 2021-07-22
If you are looking to develop a machine-learning based bot you can go with pysc2: https://github.com/deepmind/pysc2
Trax — Deep Learning with Clear Code and SpeedProject mention: Why would I want to develop yet another deep learning framework? | reddit.com/r/learnmachinelearning | 2021-09-16
A collection of machine learning examples and tutorials.Project mention: How to save an attention model for deployment/exposing to an API? | reddit.com/r/deeplearning | 2021-08-17
I've been following a course teaching how to make an attention model for neural machine translation, This is the file inside the repo. I know that I'll have to use certain functions to make the textual input be processed in encodings and tokens, but those functions use certain instances of the model, which I don't know if I should keep or not. If anyone can please take a look and help me out here, it'd be really really appreciated.
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API. (by wandb)Project mention: Should I take a second attempt at GRE with so many universities making it optional? | reddit.com/r/gradadmissions | 2021-07-24
Strong ML background with almost 3 years of experience in the field. I am frequently publishing articles as an ML author for reputed organizations such as Weights and Biases.
A fork of OpenAI Baselines, implementations of reinforcement learning algorithmsProject mention: Nvidia ISAAC gym/RL | reddit.com/r/reinforcementlearning | 2021-08-28
Code for https://arxiv.org/abs/1707.06347 found: https://github.com/hill-a/stable-baselines
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Tensorforce: a TensorFlow library for applied reinforcement learningProject mention: Advice on doing RL for Settlers of Catan? | reddit.com/r/reinforcementlearning | 2021-07-11
The most promising approach has been using the TensorForce framework (https://github.com/tensorforce/tensorforce) with a custom environment that represents a simpler game (1v1 against a bot that chooses actions randomly, no trading between players, and fixing discarding to be done automatically and at random).
Machine Learning Platform for Kubernetes (MLOps tools for experimentation and automation)Project mention: [D] Productionalizing machine learning pipelines for small teams | reddit.com/r/MachineLearning | 2021-08-08
For running experiments, http://polyaxon.com/ is a really good free open-source package that has lots of nice integrations so you can quickly run experiments in k8s but it might be overkill in some cases.
Check out the new game server:Project mention: Creating a new football game | reddit.com/r/WEPES | 2021-07-26
For fun, merging such an idea with Google's open source football research project and its AI could result in a very interesting game!
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).Project mention: How to pretrain a model on expert data? | reddit.com/r/reinforcementlearning | 2021-09-12
Try using an imitation learning algorithm. Two popular options are MaxEnt IRL and GAIL. This repository has GAIL implementation and this repository has MaxEnt IRL and GAIL implementation. There are other implementations too that you can check out.
DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.Project mention: Any beginner resources for RL in Robotics? | reddit.com/r/robotics | 2021-04-19
DeepMind's dm control: https://github.com/deepmind/dm_control
A library of reinforcement learning components and agentsProject mention: Applied resources in Pytorch? | reddit.com/r/reinforcementlearning | 2021-07-04
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.Project mention: I need suggestions to improve my project | reddit.com/r/github | 2021-09-06
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.
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.Project mention: Help understanding PPO training performance | reddit.com/r/reinforcementlearning | 2021-09-19
I'm using a simple training loop, based on this.
Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)Project mention: Rl algorithm implemented | reddit.com/r/reinforcementlearning | 2021-07-18
MuZeroProject mention: MuZero unable to solve non-slippery FrozenLake environment? | reddit.com/r/reinforcementlearning | 2021-08-09
I have used this implementation from MuZero: https://github.com/werner-duvaud/muzero-general
Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.Project mention: What sort of algorithm should I use ? Incomplete information, card game. (Flowchart for reference) | reddit.com/r/learnmachinelearning | 2021-01-12
Probably the easiest way for you to get started is to implement your game on an open source RL framework that has working implementations of some basic CFR variations as well as some other self-play algorithms such as NFSP. OpenSpiel and RLCard are two that I am aware of. Depending on the complexity of your game and how strong your agent needs to play, you might be satisfied with the performance you get using by one of these frameworks.
Minimalistic gridworld package for OpenAI GymProject mention: How to train an agent in custom mini-grid environment using stable baselines3? | reddit.com/r/reinforcementlearning | 2021-07-20
Hello guys I tried to build a custom environment using maxicymeb repo
Lightweight and scalable deep reinforcement learning using PyTorch. 🔥Project mention: ElegantRL: A Lightweight and Stable Deep Reinforcement Learning Library | news.ycombinator.com | 2021-03-15
Advanced Deep Learning with Keras, published by PacktProject mention: Cannot understand how REINFORCE model is trained | reddit.com/r/reinforcementlearning | 2021-03-04
I have understood the concept of REINFORCE algorithm and what policy gradient is. However, when I see the code published by PacktPublishing, I was stuck with it.
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras (by keon)Project mention: Deep Q Network knapsack problem | reddit.com/r/deeplearning | 2021-05-22
So go online on GitHub and find a DQN implementation that has options for using a feedforward net as input (instead of conv net as your input isn’t pixel based). Any remotely modular piece of code will take in state space size and action space as parameters to their NN. This is essentially setting input layer to be equal to state space (so 4) and output layer to be action space (201). (https://github.com/keon/deep-q-learning) this repo seems helpful i a cursory glance
A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.Project mention: [N][R] A Brief Tutorial for Developing AutoML Tools with Hypernets | reddit.com/r/MachineLearning | 2021-06-28
Please see here for the Hypernets library.
What are some of the best open-source reinforcement-learning projects in Python? This list will help you:
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