1962 Open source projects that are alternatives of or similar to Deepdrive

DrQ: Data regularized Q

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

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PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

Code repository for the Animal AI Olympics competition

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Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research

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A High Level Python Deep Reinforcement Learning library. Great for beginners, prototyping and quickly comparing algorithms

Pytorch implementation of the PAAC algorithm presented in Efficient Parallel Methods for Deep Reinforcement Learning https://arxiv.org/abs/1705.04862

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

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MuZero

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Source codes for the book "Reinforcement Learning: Theory and Python Implementation"

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

Reinforcement Learning Algorithms

PyTorch implementation of Soft Actor-Critic (SAC)

Unreal environments for reinforcement learning

This is a dynamic simulation for quadrotor UAV

Implementation of reinforcement learning approach to make a car learn to drive smoothly in minutes

Code repository for SARNet: Learning Multi-Agent Communication through Structured Attentive Reasoning (NeurIPS 2020)

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RLgraph: Modular computation graphs for deep reinforcement learning

和（he for objective-c） —— “信息熵减机系统”

Wolpertinger Training with DDPG (Pytorch), Deep Reinforcement Learning in Large Discrete Action Spaces. Multi-GPU/Singer-GPU/CPU compatible.

Code for quadrotor control

Link of ML papers to their blogs/ supplementary material

Proto-RL: Reinforcement Learning with Prototypical Representations

RAD: Reinforcement Learning with Augmented Data

Neural Symbolic Machines is a framework to integrate neural networks and symbolic representations using reinforcement learning, with applications in program synthesis and semantic parsing.

Grokking Deep Reinforcement Learning

PyTorch implementation of Trust Region Policy Optimization

PyTorch implementation of soft actor critic

[RSS 2019] End-to-End Robotic Reinforcement Learning without Reward Engineering

Self-Driving Truck in Euro Truck Simulator 2, trained via Reinforcement Learning

An experimentation framework for Reinforcement Learning using OpenAI Gym, Tensorflow, and Keras.

A reinforcement learning environment for self-driving cars in the browser.

🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2

Train robotic agents to learn to plan pushing and grasping actions for manipulation with deep reinforcement learning.

A Comprehensive Reinforcement Learning Zoo for Simple Usage 🚀

The repository hosts the code for the SBST CPS Tool competition for testing autonomous cars.

PyTorch implementations of Deep Reinforcement Learning algorithms (DQN, DDQN, A2C, VPG, TRPO, PPO, DDPG, TD3, SAC, SAC-AEA)

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A modular high-level library to train embodied AI agents across a variety of tasks, environments, and simulators.

A PyTorch reinforcement learning library for generalizable and reproducible algorithm implementations with an aim to improve accessibility in RL

Structural implementation of RL key algorithms

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Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features

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

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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