Matching Items (2)
Filtering by
Analysis of COVID-19 Incident Rate Throughout the U.S. Southwest With Respect to Stay-At-Home Orders
Description
Analyzing Incident Rates of COVID-19 Before and After Stay-At-Home Orders Throughout the Southwestern U.S. with Respect to Limited Mobility Models
ContributorsTilleman, Karl Benson (Author) / Albuquerque, Fabio Suzart de (Thesis director) / Powers, Brian (Committee member) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
In this paper, I describe the development of a unique approach to developing strategies for games in which success can only be measured by the final outcome of the game, preventing the use of heuristics. I created and evaluated evolutionary algorithms, applying them to develop strategies for tic-tac-toe. Strategies are comprised of neural networks with randomly initiated weights. A population of candidate strategies are created, each strategy competes individually against each other strategy, and evolutionary operators are applied to create subsequent generations of strategies. The set of strategies within a generation of the evolutionary algorithm forms a metagame that evolves as the algorithm progresses. Hypothesis testing shows that strategies produced by this approach significantly outperform a baseline of entirely random action, although they are still far from optimal gameplay.
ContributorsRodriguez, Julien Guillermo (Author) / Martin, Thomas (Thesis director) / Powers, Brian (Committee member) / College of Integrative Sciences and Arts (Contributor, Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05