tanvirtin/snake-neural-networks
Neural Network learning algorithm comparison using a classic game of Snake!
This project compares how different artificial intelligence techniques learn to play the classic game of Snake. It takes the game's state as input (like obstacles and apple position) and outputs the next move for the 'snake'. The goal is to see which AI method can learn to play as well as or better than an average human player, making it useful for those interested in game AI development or comparing learning algorithms.
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Use this if you are exploring how different AI learning paradigms, specifically genetic algorithms and brute-force reinforcement, perform in a controlled, simple game environment.
Not ideal if you need a plug-and-play AI for a complex, real-world application, or if you're looking for advanced game-playing AI in environments with adversaries or highly dynamic rule sets.
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10
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Language
Python
License
MIT
Category
Last pushed
Jan 07, 2019
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