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Description
Popular competitive fighting games such as Super Smash Brothers and Street Fighter have some of the steepest learning curves in the gaming industry. These incredibly technical games require the full attention of the player and often take years to master completely. This barrier of entry prevents newer players from enjoying

Popular competitive fighting games such as Super Smash Brothers and Street Fighter have some of the steepest learning curves in the gaming industry. These incredibly technical games require the full attention of the player and often take years to master completely. This barrier of entry prevents newer players from enjoying the competitive social environment that such games offer, creating a rift between casual and competitive players. Learning the rules can sometimes be more difficult than playing the game itself. To truly master these concepts requires personal attention from someone who deeply understands the core mechanics that operate behind the scenes.
Meanwhile, machine learning is growing more advanced by the day. Online retailers like Amazon run complex algorithms to recommend future purchases and monitor price changes. Mobile phones use neural networks to interpret speech. GPS apps track anonymous motion data in smartphones to give real-time traffic estimates. Artificial intelligence is becoming increasingly ubiquitous because of its versatility in analyzing and solving human problems; it follows, then, that a machine could learn how to teach humans skills and techniques. HelperBot is a platform fighting game project that employs this cutting-edge learning technology to close the skill gap between novice and veteran gamers as quickly and seamlessly as possible.
ContributorsPalermo, Seth Daniel (Author) / Olson, Loren (Thesis director) / Marinelli, Donald (Committee member) / Arts, Media and Engineering Sch T (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05