Shypd.aiThe largest open index of AI toolsDRL-FlappyBird is an open-source coding & development tool that demonstrates deep reinforcement learning by training an AI to play Flappy Bird. It uses Deep Q Learning (DQN) with TensorFlow.
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DRL-FlappyBird is an open-source project designed to showcase deep reinforcement learning principles through the classic game Flappy Bird. It implements the Deep Q Learning (DQN) algorithm, specifically leveraging TensorFlow for its neural network computations. The project aims for simplicity and clarity, making the underlying DQN code concise and easy to understand, at only 160 lines long. It includes both the NIPS 2013 and Nature Version DQN implementations. The modular design allows the core DQN class to be adapted for playing other games, providing a flexible framework for reinforcement learning experimentation. Users can easily run the code to observe an AI agent learning to play Flappy Bird.
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