I made a simple obstacle collision game in Python and made a neural network which will play the game using the NEAT (NeuroEvolution of Augmenting Topologies) and I got a final network as follows ->


    0 DefaultNodeGene(key=0, bias=-0.9866681151537819, response=1.0, activation=tanh, aggregation=sum)
    1 DefaultNodeGene(key=1, bias=-0.19684707599816334, response=1.0, activation=tanh, aggregation=sum)
    2 DefaultNodeGene(key=2, bias=-0.023412587732523353, response=1.0, activation=tanh, aggregation=sum)
    DefaultConnectionGene(key=(-3, 0), weight=0.413094212700832, enabled=True)
    DefaultConnectionGene(key=(-3, 1), weight=0.38493758445483867, enabled=True)
    DefaultConnectionGene(key=(-3, 2), weight=0.3326930938849062, enabled=True)
    DefaultConnectionGene(key=(-2, 0), weight=-1.4191333690437578, enabled=True)
    DefaultConnectionGene(key=(-2, 1), weight=-1.604381939943581, enabled=True)
    DefaultConnectionGene(key=(-2, 2), weight=-1.8972709882162406, enabled=True)
    DefaultConnectionGene(key=(-1, 1), weight=-2.030443212728862, enabled=True)  
    DefaultConnectionGene(key=(-1, 2), weight=-1.0869417163203305, enabled=True)
    DefaultConnectionGene(key=(2, 2), weight=0.6586795750845641, enabled=True)

But I don't know how to use this neural network to directly play the game, like how to implement this neural network. Please do help . Thank You in advance !!

GitHub Link to my project - Here


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