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Using Neural-evolution of Augmenting Topologies and OpenAI gym to train an AI to play SlitherIO

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SlitherIO-AI

Installation Guide

To run this program we need to install OpenAI gym at this link and OpenAI universe at this link. We are using Python 3.5, but Python 2.7 should also work for this project. Just make sure to use pip3 for Python 3.5 and pip for Python 2.7.

Next, make sure to install the proper python packages for this project.

pip3 install scipy neat-python==0.8 argparse

Running the Program

There are two files that are used to solve universe environments: network_config and main.py.

This program can be run with the following parameters:

--max-steps: The max number of steps to take per genome (timeout)

--episodes: The number of times to run a single genome. This takes the average fitness score over all episodes for one genome

--render: Renders the game while the algorithm is learning

--generations: The number of generations to evolve the network

--checkpoint: Uses a checkpoint to start the simulation

--num-cores: The number cores on your computer for parallel execution (not in --render mode)

Ex:

python3 main.py --max-steps=10000 --generations=50 --render

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Using Neural-evolution of Augmenting Topologies and OpenAI gym to train an AI to play SlitherIO

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