Game design is an art form that deals with inherently interactive artifacts. Game designers craft games (assembled from rule systems and content), but they really seek to manipulate play: the interaction between games and players. When developing new games that are similar to past games, a designer may rely on previous experience with related designs and relatively easy access to players familiar with conventional design choices. When exploratorily venturing into uncharted territory, uncovering games that afford novel modes of play, there is a need for practical and technological interventions that improve a designer's access to feedback from the unfamiliar design scenario. In the interdisciplinary space between game design, design studies, computational creativity, and symbolic artificial intelligence (AI), my program of mechanizing exploratory game design aims to amplify human creativity in game design; enable new game designs through deep, play-time design automation; and demonstrate novel tools that respect the concerns of design problems.
This dissertation advances a practice of modeling design spaces as logic programs in the answer set programming (ASP) paradigm. Answer set programs can concisely encode the key conditions of artifact appropriateness, and, paired with state of the art algorithms for combinatorial search and optimization, they yield efficient and expressively sculptable artifact generators. I present three major applications of ASP-encoded design spaces to exploratory game design: a powerful machine playtesting tool for analyzing designer-specified games, a novel game prototype employing machine-generated rulesets bound by iteratively discovered constraints, and a suite of level design automation tools that offer unprecedented control over the aesthetic and pedagogical properties of puzzles for a widely deployed educational game. This practice is further developed in a series of introductory programming and advanced modeling tutorials. By formally modeling design spaces as concise and authorable logic programs (and without the need for original algorithm design and maintenance), designer-programmers are broadly empowered to quickly build and evolve the in-house automation required by their own exploratory game design projects. These claims are backed by a spreading adoption of this practice by others and deployed applications to at-scale game design projects.
Taken as a whole, this dissertation offers new insight into the nature of game design in relation to other design disciplines, a new design research practice for understanding how design thinking can and should be mechanized, a novel model of transformational creativity suitable for discussing both humans and machines, and a set of new applications for symbolic AI that simultaneously broaden the applicability and tax the limits of this automated reasoning infrastructure.
|Commitee:||Wardrip-Fruin, Noah, Whitehead, Jim|
|School:||University of California, Santa Cruz|
|School Location:||United States -- California|
|Source:||DAI-B 74/06(E), Dissertation Abstracts International|
|Subjects:||Artificial intelligence, Computer science|
|Keywords:||Artificial intelligence, Computational creatvity, Design studies, Exploratory games, Game design, Programming languages, Symbolic logic|
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