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24 search results found

Dopamine ⭐ 10,248

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

Rl Adventure ⭐ 2,450

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

Cvpr2015 ⭐ 860

Atari Model Zoo ⭐ 187

A binary release of trained deep reinforcement learning models trained in the Atari machine learning benchmark, and a software release that enables easy visualization and analysis of models, and comparison across training algorithms.

Deep Q Learning ⭐ 154

Nips2015 Action Conditional Video Prediction ⭐ 110

Implementation of "Action-Conditional Video Prediction using Deep Networks in Atari Games"

Visualize_atari ⭐ 99

Code for our paper "Visualizing and Understanding Atari Agents" (https://goo.gl/AMAoSc)

Reinforcementlearning Atarigame ⭐ 87

Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games

Reinforcement_learning ⭐ 62

Deep Reinforcement Learning Algorithms implemented with Tensorflow 2.3

Tutorials ⭐ 51

tutorials of XAI project

Ppo Pytorch ⭐ 38

Implementation of PPO in Pytorch

Atarigrandchallenge ⭐ 36

Code for 'The Grand Atari Challenge dataset' paper

Deep Q Network ⭐ 26

Keras implementation of DQN for the MsPacman-v0 OpenAI Gym environment.

Reinforcement Learning On Google Colab ⭐ 21

Reinforcement Learning algorithm's using google-colab

Dqn Atari Agents ⭐ 18

DQN-Atari-Agents: Modularized & Parallel PyTorch implementation of several DQN Agents, i.a. DDQN, Dueling DQN, Noisy DQN, C51, Rainbow, and DRQN

Option Critic Arch ⭐ 15

Implementation of the Option-Critic Architecture

1-step Q Learning from the paper "Asynchronous Methods for Deep Reinforcement Learning"

FQF(Fully parameterized Quantile Function for distributional reinforcement learning) is a general reinforcement learning framework for Atari games, which can learn to play Atari games automatically by predicting return distribution in the form of a fully parameterized quantile function.

Pycon2018 Rl_adventure ⭐ 8

Risk And Uncertainty ⭐ 8

Code that can be used to reproduce the experiments in our paper "Estimating Risk and Uncertainty in Deep Reinforcement Learning"

Aitodinorun ⭐ 7

This reference playing atari with deep reinforcement learning and use https://blog.paperspace.com/dino-run/ code to play Google Chrome's offline Dino Run game.

Use the movements of your thumb to play Pong against a pre-trained Double-DQN-Agent. I used Google-Colab for training the pyTorch model and created the Pong environment with Pygame.

RL Agent for Atari Game Pong

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