Thesis (M. Phil.)--University of Queensland, 2002. / Includes bibliographical references.

Thesis (Ph. D.)--Ohio State University, 2004. / Title from first page of PDF file. Document formatted into pages; contains xx, 211 p.; also includes graphics Includes bibliographical references (p. 208-211). Available online via OhioLINK's ETD Center

Thesis (Ph. D.)--Ohio State University, 1986. / Includes vita. Includes bibliographical references (leaves 301-310). Available online via OhioLINK's ETD Center.

Thesis (M.S. in computer science)--Washington State University, December 2007. / Includes bibliographical references (p. 77-79).

Thesis (Ph.D.)--Bowling Green State University, 2010. / Document formatted into pages; contains v, 146 p. Includes bibliographical references.

This research addresses the challenges associated with the supervision of game development projects as part of a capstone experience. The context of this research is the capstone experience as undertaken by third year software development students who have chosen to develop a game for their project at the School of Information and Communication Technology (ICT) at the Nelson Mandela Metropolitan University (NMMU). This research begins by determining the curricular requirements with respect to the capstone experience for Information Technology (IT) qualifications. This is done by investigating the applicable documentation at the international, national and departmental levels. The position of game development as a sub-category of software development is established and the Indie paradigm is investigated as a further sub-category of game development. Furthermore, the Indie paradigm is investigated through in-depth analyses of the techniques used in the development of ten Indie games. This investigation serves to identify the commonly used techniques in the Indie paradigm. The research presents a case study of the game development projects at the School of ICT at the NMMU for the period from 2009 to 2013. This case study combined with the techniques identifed from the Indie paradigm forms the basis of the guidelines presented by this research. The guidelines are subject to a review by an industry expert. The review takes the form of an expert interview, which serves to verify the guidelines. This research concludes by demonstrating alignment with the objectives it set out to achieve and motivating the success of the research conducted.

This study investigated the relationships among children?s creativity, computer games, natural play, TV, and their structured activities daily after school by the analysis of their time spent on computer games, and the other components with the Torrance Test of Creative Thinking (TTCT), using the statistical methods of MANOVA and SEM. Activity 5 of Verbal Form B and Activity 2 of Figural Forms B of the TTCT were used to measure students? verbal and figural creativity scores. Two hundreds and thirty eight 3rd and 6th grade students from one rural and one urban school in the Republic of Korea were studied. The study also examined whether any variables (i.e., gender, grade, location, achievement, genres of computer games and parental Social Economic Status) affected children?s creativity scores and computer game usage. Children using computer games heavily showed significantly higher scores on the scale of Figural Originality than those with moderate usage. Highly structured activity students had significantly higher scores on all Figural TTCT scales than did the moderately structured activity group. There was a significant location difference on Figural Originality and Figural Elaboration, parental SES, and time spent on TV. Time spent on free play did not show any differences on any TTCT scales. Time spent on TV was differently correlated with the Figural TTCT by parental SES. Third graders obtained significantly higher scores than 6th graders on all the Verbal TTCT and Figural Elaboration scales. In this study, the subjects showed a significant preference for Role Playing Game (RPG) and Casual games. Gender differences on preferences of game genres, time spent on computer games and starting period of computer use were found. The MANOVA among genres of computer games on the TTCT scores was significant. The path models showed that the parent factor had strong correlation with children?s figural creativity and the play factor was correlated more with verbal creativity.

This study investigated the relationships among children?s creativity, computer games, natural play, TV, and their structured activities daily after school by the analysis of their time spent on computer games, and the other components with the Torrance Test of Creative Thinking (TTCT), using the statistical methods of MANOVA and SEM. Activity 5 of Verbal Form B and Activity 2 of Figural Forms B of the TTCT were used to measure students? verbal and figural creativity scores. Two hundreds and thirty eight 3rd and 6th grade students from one rural and one urban school in the Republic of Korea were studied. The study also examined whether any variables (i.e., gender, grade, location, achievement, genres of computer games and parental Social Economic Status) affected children?s creativity scores and computer game usage. Children using computer games heavily showed significantly higher scores on the scale of Figural Originality than those with moderate usage. Highly structured activity students had significantly higher scores on all Figural TTCT scales than did the moderately structured activity group. There was a significant location difference on Figural Originality and Figural Elaboration, parental SES, and time spent on TV. Time spent on free play did not show any differences on any TTCT scales. Time spent on TV was differently correlated with the Figural TTCT by parental SES. Third graders obtained significantly higher scores than 6th graders on all the Verbal TTCT and Figural Elaboration scales. In this study, the subjects showed a significant preference for Role Playing Game (RPG) and Casual games. Gender differences on preferences of game genres, time spent on computer games and starting period of computer use were found. The MANOVA among genres of computer games on the TTCT scores was significant. The path models showed that the parent factor had strong correlation with children?s figural creativity and the play factor was correlated more with verbal creativity.

M. Tech. Computer Science / This dissertation reports on the development of a new game playing technique based on Probabilistic Distance clustering (pd-clustering) method to evolve an Awale game player. Game playing is one classic and complex problems of artificial intelligence that has attracted the attention of researchers in computer science field of study.

The goal of this thesis is to explore the use of reinforcement learning (RL) in commercial computer games. Although RL has been applied with success to many types of board games and non-game simulated environments, there has been little work in applying RL to the most popular genres of games: first-person shooters, role-playing games, and real-time strategies. In this thesis we use a first-person shooter environment to create computer players, or bots, that learn to play the game using reinforcement learning techniques. / We have created three experimental bots: ChaserBot, ItemBot and HybridBot. The two first bots each focus on a different aspect of the first-person shooter genre, and learn using basic RL. ChaserBot learns to chase down and shoot an enemy player. ItemBot, on the other hand, learns how to pick up the items---weapons, ammunition, armor---that are available, scattered on the ground, for the players to improve their arsenal. Both of these bots become reasonably proficient at their assigned task. Our goal for the third bot, HybridBot, was to create a bot that both chases and shoots an enemy player and goes after the items in the environment. Unlike the two previous bots which only have primitive actions available (strafing right or left, moving forward or backward, etc.), HybridBot uses options. At any state, it may choose either the player chasing option or the item gathering option. These options' internal policies are determined by the data learned by ChaserBot and ItemBot. HybridBot uses reinforcement learning to learn which option to pick at a given state. / Each bot learns to perform its given tasks. We compare the three bots' ability to gather items, and ChaserBot's and HybridBot's ability to chase their opponent. HybridBot's results are of particular interest as it outperforms ItemBot at picking up items by a large amount. However, none of our experiments yielded bots that are competitive with human players. We discuss the reasons for this and suggest improvements for future work that could lead to competitive reinforcement learning bots.