Python Reinforcement-agent Resources

MetaDrive: Composing Diverse Driving Scenarios for Generalizable RL [ Documentation | Demo Video ] MetaDrive is a driving simulator with the following

Tensorforce: a TensorFlow library for applied reinforcement learning Introduction Tensorforce is an open-source deep reinforcement learning framework,

TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens

Human-Level Control through Deep Reinforcement Learning Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning. This imp

SenseNet is a sensorimotor and touch simulator for deep reinforcement learning research

Advantage async actor-critic Algorithms (A3C) in PyTorch @inproceedings{mnih2016asynchronous, title={Asynchronous methods for deep reinforcement lea

Deep Reinforcement Learning with pytorch & visdom Sample testings of trained agents (DQN on Breakout, A3C on Pong, DoubleDQN on CartPole, continuous A

DEPRECATION This repository is deprecated and is no longer maintaned. Please see a more recent implementation of RL for continuous control at jax-sac.

DoomNet DoomNet is a ViZDoom agent trained by reinforcement learning. The agent is a neural network that outputs a probability of actions given only p

pytoch-dqn This project is pytorch implementation of Human-level control through deep reinforcement learning and I also plan to implement the followin

CompilerGym is a library of easy to use and performant reinforcement learning environments for compiler tasks

EARL This repository provides a simple implementation of the work "Efficient Sparse Attacks on Videos using Reinforcement Learning" Example: Demo: Her

Learning Opinion Summarizers by Selecting Informative Reviews This repository contains the codebase and the dataset for the corresponding EMNLP 2021

CARLA-Roach This is the official code release of the paper End-to-End Urban Driving by Imitating a Reinforcement Learning Coach by Zhejun Zhang, Alexa

DQN-Trading This is a framework based on deep reinforcement learning for stock market trading. This project is the implementation code for the two pap

PPO is a very popular Reinforcement Learning algorithm at present. OpenAI takes PPO as the current baseline algorithm. We use the PPO algorithm to train a policy to give the best action in any situation.

gym-mtsim: OpenAI Gym - MetaTrader 5 Simulator MtSim is a simulator for the MetaTrader 5 trading platform alongside an OpenAI Gym environment for rein

safe-control-gym Physics-based CartPole and Quadrotor Gym environments (using PyBullet) with symbolic a priori dynamics (using CasADi) for learning-ba

This repo contains self-contained RL implementations

Decentralized Reinforcement Learning This is the code complementing the paper Decentralized Reinforcment Learning: Global Decision-Making via Local Ec

Trajectory Transformer Code release for Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are in envir

rl: An efficient framework for reinforcement learning Requirements Introduction PPO Test Requirements name version Python =3.7 numpy =1.19 torch =1

WarpDrive is a flexible, lightweight, and easy-to-use open-source reinforcement learning (RL) framework that implements end-to-end multi-agent RL on a single GPU (Graphics Processing Unit).

CrowdNav with Social-NCE This is an official implementation for the paper Social NCE: Contrastive Learning of Socially-aware Motion Representations by

NEWLY ADDED A3G A NEW GPU/CPU ARCHITECTURE OF A3C FOR SUBSTANTIALLY ACCELERATED TRAINING!! RL A3C Pytorch NEWLY ADDED A3G!! New implementation of A3C

neural-combinatorial-rl-pytorch PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning. I have implemented the basic

This is code repo for our EMNLP 2017 paper "Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback", which implements the A2C algorithm on top of a neural encoder-decoder model and benchmarks the combination under simulated noisy rewards.

pytorch-a2c-ppo-acktr Update (April 12th, 2021) PPO is great, but Soft Actor Critic can be better for many continuous control tasks. Please check out

Categorical DQN. Implementation of the Categorical DQN as described in A distributional Perspective on Reinforcement Learning. Thanks to @tudor-berari

gym-recsys: Customizable RecSys Simulator for OpenAI Gym Installation | How to use | Examples | Citation This package describes an OpenAI Gym interfac

MINERVA is an out-of-the-box GUI tool for offline deep reinforcement learning, designed for everyone including non-programmers to do reinforcement learning as a tool.

Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay This is the official implementation of our paper "Diversity-based Traje

DockStream Description DockStream is a docking wrapper providing access to a collection of ligand embedders and docking backends. Docking execution an

Orthrus is a macOS agent that uses Apple's MDM to backdoor a device using a malicious profile. It effectively runs its own MDM server and allows the operator to interface with it using Mythic.

SOFA This repository is the implementation of SOFA, the Simulator for OFfline leArning and evaluation. Keeping Dataset Biases out of the Simulation: A

IVOS-W Paper Learning to Recommend Frame for Interactive Video Object Segmentation in the Wild Zhaoyun Yin, Jia Zheng, Weixin Luo, Shenhan Qian, Hanli

Language Emergence in Multi Agent Dialog Code for the Paper Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog Satwik Kottur, José M.

Rainbow Rainbow: Combining Improvements in Deep Reinforcement Learning [1]. Results and pretrained models can be found in the releases. DQN [2] Double

Off-Policy Multi-Agent Reinforcement Learning (MARL) Algorithms This repository contains implementations of various off-policy multi-agent reinforceme

Gated-Attention Architectures for Task-Oriented Language Grounding This is a PyTorch implementation of the AAAI-18 paper: Gated-Attention Architecture

PyTorch implementation of TRPO Try my implementation of PPO (aka newer better variant of TRPO), unless you need to you TRPO for some specific reasons.

Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.

Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.

Emergent Translation in Multi-Agent Communication PyTorch implementation of the models described in the paper Emergent Translation in Multi-Agent Comm

Advanced Deep Learning with TensorFlow 2 and Keras (Updated for 2nd Edition)

Quantile Regression DQN Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression (https://arx

Learning to Communicate with Deep Multi-Agent Reinforcement Learning This is a PyTorch implementation of the original Lua code release. Overview This

Deep Reinforcement Learning Algorithms with PyTorch This repository contains PyTorch implementations of deep reinforcement learning algorithms and env

GAM ⠀⠀ A PyTorch implementation of Graph Classification Using Structural Attention (KDD 2018). Abstract Graph classification is a problem with practic

DrQ-v2: Improved Data-Augmented RL Agent Method DrQ-v2 is a model-free off-policy algorithm for image-based continuous control. DrQ-v2 builds on DrQ,

Medusa Medusa is a cross-platform agent compatible with both Python 3.8 and Python 2.7. Installation To install Medusa, you'll need Mythic installed o

Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr

Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these environments (PPO, SAC, evolutionary strategy, and direct trajectory optimization are implemented).

Pacman Search Artificial Intelligence search algorithm base on Pacman Source The Pacman Projects by the University of California, Berkeley. Layouts Di

pytorch-a3c-mujoco Disclaimer: my implementation right now is unstable (you ca refer to the learning curve below), I'm not sure if it's my problems. A

The Malmo Collaborative AI Challenge - Team Pig Catcher Approach The challenge involves 2 agents who can either cooperate or defect. The optimal polic

AlphaZero-Gomoku This is an implementation of the AlphaZero algorithm for playing the simple board game Gomoku (also called Gobang or Five in a Row) f

Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments [Project website] [Paper] This project is a PyTorch

Mava: a research framework for distributed multi-agent reinforcement learning Table of Contents Overview Getting Started Supported Environments System

DI-HPC: Decision Intelligence - High Performance Computation DI-HPC is an acceleration operator component for general algorithm modules in reinforceme

DI Orchestrator DI Orchestrator is designed to manage DI (Decision Intelligence) jobs using Kubernetes Custom Resource and Operator. Prerequisites A w

Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch. 🔥

gym-anm is a framework for designing reinforcement learning (RL) environments that model Active Network Management (ANM) tasks in electricity distribution networks. It is built on top of the OpenAI Gym toolkit.

LibraNet This repository includes the official implementation of LibraNet for crowd counting, presented in our paper: Weighing Counts: Sequential Crow

Recurrent Fast Weight Programmers This is the official repository containing the code we used to produce the experimental results reported in the pape

Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these environments (PPO, SAC, evolutionary strategy, and direct trajectory optimization are implemented).

PyTorch code to reproduce LyDROO algorithm [1], which is an online computation offloading algorithm to maximize the network data processing capability subject to the long-term data queue stability and average power constraints. It applies Lyapunov optimization to decouple the multi-stage stochastic MINLP into deterministic per-frame MINLP subproblems and solves each subproblem via DROO algorithm. It includes:

BridgeWalk is a partially-observed reinforcement learning environment with dynamics of varying stochasticity. The player needs to walk along a bridge to reach a goal location. When the player walks off the bridge into the water, the current will move it randomly until it gets washed back on the shore. A good agent in this environment avoids this stochastic trap

Pretraining Representations For Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Ch

Megaverse Megaverse is a new 3D simulation platform for reinforcement learning and embodied AI research. The efficient design of the engine enables ph

This repository is the implementation of the paper "Thermal Control of Laser Powder Bed Fusion Using Deep Reinforcement Learning", linked here. The project makes use of the Deep Reinforcement Library stable-baselines3 to derive a control policy that maximizes melt pool depth consistency.

[ICML 2021] DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning | 斗地主AI

CowHerd is a partially-observed reinforcement learning environment, where the player walks around an area and is rewarded for milking cows. The cows try to escape and the player can place fences to help capture them. The implementation of CowHerd is based on the Crafter environment.

MALib: A parallel framework for population-based multi-agent reinforcement learning MALib is a parallel framework of population-based learning nested

Deep Reinforcement Learning Library built on top of Neural Network Libraries NNablaRL is a deep reinforcement learning library built on top of Neural

[ICML 2021] DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning DouZero is a reinforcement learning framework for DouDizhu (斗地主), t

On the model-based stochastic value gradient for continuous reinforcement learning This repository is by Brandon Amos, Samuel Stanton, Denis Yarats, a

Optimal Model Design for Reinforcement Learning This repository contains JAX code for the paper Control-Oriented Model-Based Reinforcement Learning wi

banditml is a lightweight contextual bandit & reinforcement learning library designed to be used in production Python services. This library is developed by Bandit ML and ex-authors of Facebook's applied reinforcement learning platform, Reagent.

MATP-solver Simulator collision check path step random initial states or given states Traditional method Seperate A* algorithem Confict-based Search S

Summary Loop This repository contains the code for ACL2020 paper: The Summary Loop: Learning to Write Abstractive Summaries Without Examples. Training

Maria: A Visual Experience Powered Conversational Agent This repository is the Pytorch implementation of our paper "Maria: A Visual Experience Powered

Due to a normalization bug the expert trajectories have lower performance than the rl_baseline_zoo reported experts. Please see the following link in

Decision Transformer Lili Chen*, Kevin Lu*, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas†, and Igor M

🔬 A curated list of awesome machine learning strategies & tools in financial market.

Narya The Narya API allows you track soccer player from camera inputs, and evaluate them with an Expected Discounted Goal (EDG) Agent. This repository

This repo contains code for our paper State-only Imitation with Transition Dynamics Mismatch published at ICLR 2020. The code heavily uses the RL mach

AndroidEnv is a Python library that exposes an Android device as a Reinforcement Learning (RL) environment.

AutoPentest-DRL: Automated Penetration Testing Using Deep Reinforcement Learning AutoPentest-DRL is an automated penetration testing framework based o

House-GAN++ Code and instructions for our paper: House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent

Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr

When2com: Multi-Agent Perception via Communication Graph Grouping This is the PyTorch implementation of our paper: When2com: Multi-Agent Perception vi

Hybrid solving process for combinatorial optimization problems Combinatorial optimization has found applications in numerous fields, from aerospace to

Paddle-RLBooks Welcome to Paddle-RLBooks which is a reinforcement learning code study guide based on pure PaddlePaddle. 欢迎来到Paddle-RLBooks，该仓库主要是针对强化学

CURL Rainbow Status: Archive (code is provided as-is, no updates expected) This is an implementation of CURL: Contrastive Unsupervised Representations

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

RoboDesk A Multi-Task Reinforcement Learning Benchmark If you find this open source release useful, please reference in your paper: @misc{kannan2021ro

MALib A general-purpose multi-agent training framework. Installation step1: build environment conda create -n malib python==3.7 -y conda activate mali

Reinforcement Learning (PyTorch) 🤖 + 🍰 = ❤️ This repo will contain PyTorch implementation of various fundamental RL algorithms. It's aimed at making

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.