DeepLearningFlappyBird | Flappy Bird hack using Deep Reinforcement Learning ( Deep Q | Machine Learning library

 by   yenchenlin Python Version: Current License: MIT

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.
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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.
              OutlinedDot
              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.

            kandi-Quality Quality

              DeepLearningFlappyBird has 0 bugs and 0 code smells.

            kandi-Security 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.

            kandi-License 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.

            kandi-Reuse Reuse

              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 08:23

            Every action has a Q_value.

            And the action input a is one-hot.

            So this line is to choose the 'hot' Q_value.

            Source https://stackoverflow.com/questions/43536573

            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

            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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            https://github.com/yenchenlin/DeepLearningFlappyBird.git

          • CLI

            gh repo clone yenchenlin/DeepLearningFlappyBird

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            git@github.com:yenchenlin/DeepLearningFlappyBird.git

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