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I am new in the field of AI. I am working to create the flappy bird using Genetic Algorithm. After reading and seeing some examples, I saw that most implementations use a Neural Network + Genetic Algorithm and after certain generations, you achieve a very good agent that survives very long.

I currently struggling to implement the Neural Network since I have never taken a Machine Learning course. On many examples that I have read neural networks require training inputs and outputs. For the flappy bird, I can't think of output since you don't really know if the action of flapping will benefit you or not.

In the example that I followed, Synaptic.js is used and it is pretty straight-forward. However, in Python, I can't find a simple library that will initialize randomly and adjust the weights and biases depending on the good agents that survive longer.

What would be the right way to implement this Neural Network without having a training dataset?

Is there any way to create Flappy Bird without using Neural Networks, just Genetic Algorithm?

The example in Javascript that I am referring to: Flappy Bird Using Machine Learning

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I agree a neural net is a good start and you might want to add a constitutional neural network to list of models you want to test and evaluate.

However your question was really on getting something up and running using python. I don't have enough time for me to play games, much more let my computers do it for me... but I know someone who has done such a project.

Hopefully that helps.

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I would recommend learning about Reinforcement learning first. You don't need a dataset as you train your network by letting it play the game over and over again. but knowing how to do so doea mean finding out about markov decision process and how you can use the neural network to solve this.

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