641 Open source projects that are alternatives of or similar to Rosettastone

Explore and find reinforcement learning environments in a list of 150+ open source environments.

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

AI Research Platform for Reinforcement Learning from Real Panoramic Images.

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Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019

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An environment to high-frequency trading agents under reinforcement learning

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AI research environment for the Atari 2600 games 🤖.

A PyTorch Library for Reinforcement Learning Research

RAD: Reinforcement Learning with Augmented Data

ROS 2 enabled Machine Learning algorithms

PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

A universal flight control tuning framework

A curated list of Monte Carlo tree search papers with implementations.

A collection of pre-trained RL agents using Stable Baselines3, training and hyperparameter optimization included.

Python library for Reinforcement Learning.

MuZero

Use AWS RoboMaker and demonstrate running a simulation which trains a reinforcement learning (RL) model to drive a car around a track

Mirror of Stable-Baselines: a fork of OpenAI Baselines, implementations of reinforcement learning algorithms

Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms

Implementation of selected reinforcement learning algorithms in Tensorflow. A3C, DDPG, REINFORCE, DQN, etc.

Unrailed! simulator using C++ with some reinforcement learning and Unrailed! AI using Python with OpenCV

gym-gazebo2 is a toolkit for developing and comparing reinforcement learning algorithms using ROS 2 and Gazebo

A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.

ELF: a platform for game research with AlphaGoZero/AlphaZero reimplementation

An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)

DrQ: Data regularized Q

Implementation of Inverse Reinforcement Learning (IRL) algorithms in python/Tensorflow. Deep MaxEnt, MaxEnt, LPIRL

A curated awesome list of AI Startups in India & Machine Learning Interview Guide. Feel free to contribute!

JSON files for Hearthstone - Website code

Deep Q-learning for playing flappy bird game

Reimplementation of World-Models (Ha and Schmidhuber 2018) in pytorch

A curated list of awesome links and software libraries that are useful for robots.

Arnold - DOOM Agent

Keras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

Quiz & Assignment of Coursera

Python implementations of contextual bandits algorithms

Reinforcement learning with unsupervised auxiliary tasks

AutoKernel 是一个简单易用，低门槛的自动算子优化工具，提高深度学习算法部署效率。

Implementations of Reinforcement Learning Models in Tensorflow

S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics

Paper reading notes on Deep Learning and Machine Learning

Deep-learning by using Pytorch. Basic nns like Logistic, CNN, RNN, LSTM and some examples are implemented by complex model.

Poker engine for poker AI development in Python

cuDF - GPU DataFrame Library

A course in reinforcement learning in the wild

A collection of reference machine learning and optimization models for enterprise operations: marketing, pricing, supply chain

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

Repo for the Deep Reinforcement Learning Nanodegree program

Self-driving car simulator for the Duckietown universe

Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II

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Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

HoME: a Household Multimodal Environment is a platform for artificial agents to learn from vision, audio, semantics, physics, and interaction with objects and other agents, all within a realistic context.

In this paper, we implement three state-of-art continuous reinforcement learning algorithms, Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimization (PPO) and Policy Gradient (PG)in portfolio management.