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PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..

Deep Learning and Reinforcement Learning Library for Scientists

MARS is shortened for Multi-Agent Research Studio, a library for mulit-agent reinforcement learning research.

Official implementation for: Consistency Models as a Rich and Efficient Policy Class for Reinforcement Learning ICLR'24

Apply deep reinforcement learning methods including DQN, DDPG for traffic light control in simulation (discrete environment), to prove the 'Green Wave' phenomenon in intelligent traffic system.

Q-network with cross-entropy (CE) method for reinforcement learning.

Open-source code for paper CDT: Cascading Decision Trees for Explainable Reinforcement Learning

Benchmark present methods for efficient reinforcement learning. Methods include Reptile, MAML, Residual Policy, etc. RL algorithms include DDPG, PPO.

Official code (simulation part) for paper Sim-to-Real Transfer for Robotic Manipulation with Tactile Sensory Zihan Ding, Ya-Yen Tsai, Wang Wei Lee, Bidan Huang International Conference on Intelligent Robots and Systems (IROS) 2021

Official code of Nash-DQN for paper: Nash-DQN algorithm for two-player zero-sum Markov games, details see our paper: A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games. Zihan Ding, Dijia Su, Qinghua Liu, Chi Jin

Reinforcement Learning for RLBench

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Sigle qubit state discrimination with machine learning method (neural networks); An on board implementation with vivado FPGA + ARM, for fast qubit discrimination and feedback control in real physics system.

A simple OpenAI Gym environment for single and multi-agent reinforcement learning

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Official implementation of "Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning" (arXiv:2402.03570)

FinRL: The first open-source project for financial reinforcement learning. Please star. 🔥

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This is a fork of Surreal Robotics Suite that enables support to domain randomization and inverse kinematics (IK).

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Code for paper Not Only Domain Randomization: Universal Policy with Embedding System Identification.

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This project aim to reproduce Sora (Open AI T2V model), we wish the open source community contribute to this project.

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Pytorch based codes. Implementations of most popular algorithms at present.

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A toolkit for robot learning research.

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Implementation of Multi-Game Decision Transformers in PyTorch

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This is a library that provides dual dexterous hand manipulation tasks through Isaac Gym

[CVPR2024 Highlight] VBench - We Evaluate Video Generation

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Topic Modelling for Humans

This is an AI agent for Street Fighter II Champion Edition.

Code to borrow as much { WETH, USDC, DAI, USDT } as you want from Aave and make an arbitrage transaction with Uniswap up to V3

Unofficial Implementation of Consistency Models in pytorch

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Muesli RL algorithm implementation (PyTorch) (LunarLander-v2)

Cloud-native Deep Reinforcement Learning. Please star. 🔥

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A collection of basic modules used in robotics.

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

Productive & portable high-performance programming in Python.

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《机器学习系统：设计与实现》

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A simple neural network for python autocompletion

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:alarm_clock: AI conference deadline countdowns

Code to trade the financial markets using Contextual Bandits

Rocket-recycling with Reinforcement Learning

Make it easy to specify simple MDPs that are compatible with the OpenAI Gym.

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Sphinx theme for readthedocs.org

Implementation of Deep Reinforcement Learning from Self-Play in Imperfect-Information Games (Heinrich and Silver, 2016)

The pure and clear PyTorch Distributed Training Framework.

Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

This project is for learning and researching on Deep RL. Maintained by University AI researchers.

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PRML algorithms implemented in Python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent

Distilling a Neural Network Into a Soft Decision Tree., Nicholas Frosst, Geoffrey Hinton., 2017.

Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet

A game theoretic approach to explain the output of any machine learning model.

Book about interpretable machine learning

《动手学深度学习》：面向中文读者、能运行、可讨论。英文版即伯克利“深度学习导论”教材。

Sequence modeling benchmarks and temporal convolutional networks

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研究资源列表 A curated list of research resources

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Implementation of advantage-weighted regression.

Simulation of spiking neural networks (SNNs) using PyTorch.

A3C LSTM Atari with Pytorch plus A3G design

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Autoregressive policies for continuous control reinforcement learning

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Gym environments for Robots that learn to interact with the environment autonomously

Deep Reinforcement Learning Framework + Algorithms

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Tensorflow implementation of a Deep Distributed Distributional Deterministic Policy Gradients (D4PG) network, trained on OpenAI Gym environments.

Starter Kit for the NeurIPS 2019 Disentanglement Challenge

Evolutionary Algorithm using Python

Build your neural network easy and fast

机器学习相关教程

Bayesian Reinforcement Learning in Tensorflow

Reinforcement learning environments with musculoskeletal models

The Winning Solution for the Learning To Run Challenge 2017

A community repository for benchmarking Bayesian methods

A set of high-dimensional continuous control environments for use with Unity ML-Agents Toolkit.

PyTorch Agent Net: reinforcement learning toolkit for pytorch

Hands-on Deep Reinforcement Learning, published by Packt

Python3 ROS Interface to Rethink Sawyer Robots with OpenAI Gym Compatibility

High-Resolution Network for Photorealistic Style Transfer

Implementation of Efficient Off-policy Meta-learning via Probabilistic Context Variables (PEARL)

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Real numbers, data science and chaos: How to fit any dataset with a single parameter

Neural MMO - A Massively Multiagent Game Environment

PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay

An educational resource to help anyone learn deep reinforcement learning.

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains.

A collection of my learning notes

A curated list of Meta-Learning resources/papers.

PyTorch implementation of TD3 and DDPG for OpenAI gym tasks

A Python implementation of global optimization with gaussian processes.

Progressive Growing of GANs for Improved Quality, Stability, and Variation

StarCraft II Learning Environment

Efficient Batched Reinforcement Learning in TensorFlow

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO) and Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR).

Automatic coloring and shading of manga-style lineart, using Tensorflow + cGANs

random search, hill climbing, policy gradient

PyTorch implementation of MAML: https://arxiv.org/abs/1703.03400

Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch

Code for RL experiments in "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

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Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL

Chainer implementation of adversarial autoencoder (AAE)

Tensor GAN

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Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

TensorFlow Tutorials with YouTube Videos

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Variational Auto-Encoder with Convolutional Neural Network

verilog modules

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A toolkit for developing and comparing reinforcement learning algorithms.

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

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Web interface for browsing, search and filtering recent arxiv submissions

TensorLy: Tensor Learning in Python.

RNNLIB is a recurrent neural network library for sequence learning problems. Forked from Alex Graves work http://sourceforge.net/projects/rnnl/

An implementation of the ideas from this paper https://arxiv.org/pdf/1803.10122.pdf

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Machine learning algorithms for many-body quantum systems

Tensorflow tutorial from basic to hard

TensorFlow Tutorial and Examples for Beginners with Latest APIs

Deep Learning Tutorial notes and code. See the wiki for more info.

Deep Learning (Python, C, C++, Java, Scala, Go)

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Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

Models and examples built with TensorFlow

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LaTeX template for USTC thesis v3.0

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A collection of deep learning tutorials using Tensorflow and Python

Python implementation of Reinforcement Learning: An Introduction

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rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.

Hacks for training RL systems from John Schulman's lecture at Deep RL Bootcamp (Aug 2017)

Reinforcement learning tutorials