Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Drl Flappybird | 536 | 3 years ago | 5 | Python | ||||||
Playing Flappy Bird Using Deep Reinforcement Learning (Based on Deep Q Learning DQN using Tensorflow) | ||||||||||
Reinforcement Learning Algorithms | 407 | 2 years ago | 4 | Python | ||||||
This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress) | ||||||||||
Flappy Bird Deep Q Learning Pytorch | 407 | 2 years ago | 4 | mit | Python | |||||
Deep Q-learning for playing flappy bird game | ||||||||||
Deeplearningforfun | 335 | 9 months ago | mit | Scala | ||||||
Implementation of some interesting ideas of deeplearning. | ||||||||||
Flappybirdlearning | 44 | 7 years ago | JavaScript | |||||||
Use deep learning to auto play flappy bird | ||||||||||
Flappybird Es | 31 | 6 years ago | 1 | Python | ||||||
An AI agent Learning to play Flappy Bird using Evolution Strategies and deep learning models. | ||||||||||
Playing Custom Games Using Deep Learning | 22 | 5 years ago | Python | |||||||
Implementation of Google's paper on playing atari games using deep learning in python. | ||||||||||
Neuroevolution Flappy Bird | 15 | 5 years ago | mit | Jupyter Notebook | ||||||
A comparison between humans, neuroevolution and multilayer perceptrons playing Flapy Bird implemented in Python | ||||||||||
Deep Q Learning Flappy Bird | 6 | 7 years ago | mit | JavaScript | ||||||
Flappybird Nueralnetwork | 4 | 6 years ago | Python | |||||||
Using Deep Q Network to play Flappy Bird |
See our video demo on YouTube Video Demo
Want to train a Flappy Bird?
Deep Q Learning algorithm is originally described in Playing Atari with Deep Reinforcement Learning, a paper from NIPS 2013 Deep Learning Workshop from DeepMind.
In this repository, instead of Atari games, we try to play with Flappy Bird. We use an open source JavaScript library ConvNetJS to train Deep Learning Models.
Our implementation follows Deep Q Learning Demo
Our goal is to train a deep neural network with q-learning technique to learn control policy from inputs generated by the game. Over time, the flappy bird learns to flap or not at a point to avoid as many pipes as possible.