Automated design of voting rules using neural networks - written in order to satisfy the requirements of the honors program at Oberlin College. Thesis and presentation included.
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Commands to run experiments for 3 candidates and 20 voters in
Main_nC3.sh, and 5 candidates and 40-80 voters onMain_nC5.sh. -
To generate preference profiles, run the commands at the top /automated_voting/voting/profiles.py
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To test baselines, run the commands at the top of /automated_voting/voting/election.py
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To test neural network, look into /automated_voting/algorithms/neural_network.py
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To run everything look into main.py
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Main thesis
More details to come soon.