464 Open source projects that are alternatives of or similar to DRL_in_CV

Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math

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Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

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..

[INACTIVE] A collection of various machine learning solver. The library is an object-oriented approach (baked with Typescript) and tries to deliver simplified interfaces that make using the algorithms pretty simple.

强化学习中文教程，在线阅读地址：https://datawhalechina.github.io/easy-rl/

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Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

TensorFlow A2C to solve Acrobot, with synchronized parallel environments

Combining deep learning and reinforcement learning.

Playing Atari games with TensorFlow implementation of Asynchronous Deep Q-Learning

A framework where a deep Q-Learning Reinforcement Learning agent tries to choose the correct traffic light phase at an intersection to maximize traffic efficiency.

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

Trained A Convolutional Neural Network To Play 2048 using Deep-Reinforcement Learning

Deep Reinforcement Learning Pong Agent, King Pong, he's the best

Solutions of assignments of Deep Reinforcement Learning course presented by the University of California, Berkeley (CS285) in Pytorch framework

PyTorch implementation of some reinforcement learning algorithms: A2C, PPO, Behavioral Cloning from Observation (BCO), GAIL.

Automate swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to choose an action to sell, buy, or hold the stocks to maximize the gain in asset value. The paper also acknowledges the need for a system that predicts the trend in stock value to work along with the reinforcement …

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Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.

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

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".

DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)

Deep reinforcement learning using baidu PARL(maze,flappy bird and so on)

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

Highly Modular and Scalable Reinforcement Learning

Paddle-RLBooks is a reinforcement learning code study guide based on pure PaddlePaddle.

A deep reinforcement learning bot that plays tetris

Lightweight deep RL Libraray for continuous control.

Scalable, event-driven, deep-learning-friendly backtesting library

The page of the Ural Federal University course "Reinforcement Learning and Neural Networks"

Reinforcement Learning Demos

Mxnet implementation of Deep Reinforcement Learning papers, such as DQN, PG, DDPG, PPO

source code for 'Improving automatic source code summarization via deep reinforcement learning'

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

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.

playing idealized trading games with deep reinforcement learning

Play Google Chrome's T-rex game with TensorFlow

Implementations of Reinforcement Learning Models in Tensorflow

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

Minimal and Clean Reinforcement Learning Examples

Deep & Classical Reinforcement Learning + Machine Learning Examples in Python

A course in reinforcement learning in the wild

"Good Robot! Now Watch This!": Repurposing Reinforcement Learning for Task-to-Task Transfer; and “Good Robot!”: Efficient Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer

Research into controllers for 2d and 3d Active Ragdolls (using MujocoUnity+ml_agents)

Course material for the DevOps with Kubernetes free MOOC by the University of Helsinki

JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"

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Course notes for Data Science related topics, prepared in LaTeX

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This is a practical resource that makes it easier to learn about and apply Practical Deep Reinforcement Learning (DRL) https://ibrahimsobh.github.io/Practical-DRL/

Reinforcement Learning algorithm's using google-colab

Operations Research Application Project - Flow Shop Scheduling Based On Reinforcement Learning Algorithm

Code and data for "Deep Reinforcement Learning of Marked Temporal Point Processes", NeurIPS 2018