Date of Award

6-2011

Document Type

Open Access

Degree Name

Bachelor of Science

Department

Computer Science

First Advisor

John Rieffel

Language

English

Keywords

game, design, development, happiness, fun

Abstract

Every one wants to play a fun game, but ”fun” is a subjective quality. Flow, a psychological theory to define what ”fun” is, states that, for an activity to be considered fun, the chal-lenge it presents must correlate with that participant’s abilities such that the activity is neither too easy or too difficult. One of the biggest problems for game designers is balancing the difficulty of its content in such a way that it appeals to the largest audience possible. In order to broaden audiences, de-velopers need to invest effort into creating numerous, discrete balances that are aligned to varying difficulty normals. Even then, these discrete categories never exactly match more than a few people’s abilities. Previous research has created systems to adjust online, chang-ing the difficulty the system throws at a player as the he or she plays the game. Creators of these systems often state that more complex evolutionary methods, like genetic algorithms, cannot be viable for such online learning due to lacking effi-ciency and effectiveness. However, newer techniques like the use of generative grammatical encodings have been shown to break such previous stereotypes of non-efficiency, creating the possibility that they might be now be a viable option. In my research, I implement a game system that uses an inter-active genetic algorithm, further using generative grammati-cal encodings, as a proof of concept that such a system can noticeably balance a game’s difficulty online, to any given player. This effect is backed up with test results from the field as to how players felt it adjusted to them.

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