Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Playing Flappy Bird Using Deep Reinforcement Learning (Based on Deep Q Learning DQN using Tensorflow)
| Date | Stars |
|---|---|
| 2026-07-31 | 585 |
| 2026-08-02 | 585 |
| 2026-08-03 | 585 |
| 2026-08-06 | 585 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
## Playing Flappy Bird Using Deep Reinforcement Learning (Based on Deep Q Learning DQN) ## Include NIPS 2013 version and Nature Version DQN I rewrite the code from another repo and make it much simpler and easier to understand Deep Q Network Algorithm from DeepMind The code of DQN is only 160 lines long. To run the code, just type python FlappyBirdDQN.py Since the DQN code is a unique class, you can use it to play other games. ## About the code As a reinforcement learning problem, we knows we need to obtain observations and output actions, and the 'brain' do the processing work. Therefore, you can easily understand the BrainDQN.py code. There are three interfaces: 1. getInitState() for initialization 2. getAction() 3. setPerception(nextObservation,action,reward,terminal) the game interface just need to be able to feed the action to the game and output observation,reward,terminal ## Disclaimer This work is based on the repo: [yenchenlin1994/DeepLearningFlappyBird](https://github.com/yenchenlin1994/DeepLearningFlappyBird.git)
Excerpt of 1,056 characters
Read on GitHub
Kan Wu · China
1
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:c0ac30e72debf530, desc:reinforcement learning, desc:q-learning