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Design Out Helplessness: AI Interventions for Game Inclusivity

Creative Commons 'BY' version 4.0 license
Abstract

There are no single-player videogames. When someone plays a game, they are not only interacting with the game's contents, but also engaging with the culture and connections that are built around that game. This channel by which people connect to one another gets cut off when the design of the game leaves a player feeling helpless and excluded. Informed by approaches from game studies, human computer interaction, and artificial intelligence (AI) research, this dissertation explores how we can fight this unintended exclusion.

From a theoretical standpoint, this work expands our vocabulary of failures in games, allowing us to differentiate in-loop from out-of-loop failures. It teaches how to design AI-powered assistance methods, allowing us to repurpose game-playing AI agents in service of game inclusivity. From a technical standpoint this work contributes three prototype systems: a dynamic tutorial framework, enabling games to respond to the skill levels of players; an AI intervention for motor accessibility, helping players to adapt dexterity based games for deliberative play; and a reinforcement learning-based navigation agent, enabling access to a portfolio of assistance methods.

As a whole, this dissertation constitutes a step towards making games more inclusive, not for the sake of games, but for the sake of the people who play them.

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