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Evolution of simple organisms with neural networks

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About Evolution of simple organisms with neural networks

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This program simulates an environment in which simple organisms with brains can evolve. The brains are directed graphs with nodes as the neurons and edges as axon/dendrite pairs. The neural network is simulated fully with each signal traveling down the edges, instead of having the conventional approach where all neurons are updated per simulation tick. The DNA is composed of: the structure of the brain, (i.e. the set of existing edges) parameters for neurons (firing threshold, excitation decay rate), and edges (speed, strength) Genetic algorithm with sexual reproduction is used to find brains that maximize the number of simulation ticks that an organism survives. Programmed in Python, Pygame library is used for drawing.

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