DeepLearningFlappyBird | Flappy Bird hack using Deep Reinforcement Learning ( Deep Q | Machine Learning library
kandi X-RAY | DeepLearningFlappyBird Summary
kandi X-RAY | DeepLearningFlappyBird Summary
DeepLearningFlappyBird is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow applications. DeepLearningFlappyBird has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However DeepLearningFlappyBird build file is not available. You can download it from GitHub.
This project follows the description of the Deep Q Learning algorithm described in Playing Atari with Deep Reinforcement Learning [2] and shows that this learning algorithm can be further generalized to the notorious Flappy Bird.
This project follows the description of the Deep Q Learning algorithm described in Playing Atari with Deep Reinforcement Learning [2] and shows that this learning algorithm can be further generalized to the notorious Flappy Bird.
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DeepLearningFlappyBird has a medium active ecosystem.
It has 6414 star(s) with 2047 fork(s). There are 285 watchers for this library.
It had no major release in the last 6 months.
There are 25 open issues and 29 have been closed. On average issues are closed in 70 days. There are 10 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of DeepLearningFlappyBird is current.
Quality
DeepLearningFlappyBird has 0 bugs and 0 code smells.
Security
DeepLearningFlappyBird has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
DeepLearningFlappyBird code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
DeepLearningFlappyBird is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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DeepLearningFlappyBird releases are not available. You will need to build from source code and install.
DeepLearningFlappyBird has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions, examples and code snippets are available.
Top functions reviewed by kandi - BETA
kandi has reviewed DeepLearningFlappyBird and discovered the below as its top functions. This is intended to give you an instant insight into DeepLearningFlappyBird implemented functionality, and help decide if they suit your requirements.
- Play a game
- Train the network
- Forward one step
- Create the network
- Checks if a player is a crash
- Return True if two pixels collide with the same pixel
- Generate a random pipe
- Bias Variable
- Creates a weight variable
- 2d convolution layer
- Max pooling op
- Load sprite images
- Gets the hit mask for the given image
Get all kandi verified functions for this library.
DeepLearningFlappyBird Key Features
No Key Features are available at this moment for DeepLearningFlappyBird.
DeepLearningFlappyBird Examples and Code Snippets
No Code Snippets are available at this moment for DeepLearningFlappyBird.
Community Discussions
Trending Discussions on DeepLearningFlappyBird
QUESTION
Can not understand this line of a popular deep Q learning program
Asked 2017-Apr-21 at 08:23
https://github.com/yenchenlin/DeepLearningFlappyBird/blob/master/deep_q_network.py#L82
I have spend a lot of time to understand it.
Why use tf.multiply
?
I can not find the math that support this multiply operation.
...ANSWER
Answered 2017-Apr-21 at 08:23Every action has a Q_value.
And the action input a
is one-hot.
So this line is to choose the 'hot' Q_value.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install DeepLearningFlappyBird
Python 2.7 or 3
TensorFlow 0.7
pygame
OpenCV-Python
TensorFlow 0.7
pygame
OpenCV-Python
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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