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Title of Thesis

Measuring Entertainment and Automatic Generation of Entertaining Games

Author(s)

Zahid Halim

Institute/University/Department Details
Department of Computer Science / Fast-National University of Computer and Emerging Sciences, Islamabad
Session
2010
Subject
Computer Science
Number of Pages
147
Keywords (Extracted from title, table of contents and abstract of thesis)
Technology, Decrease, Techniques, Entertainment, Measuring, Metrics, Entertaining, Optimized, Games, Automatic, Resources, Generation

Abstract
With the advancement in technology and decrease in prices of electronic items, Personal Computers (PCs) are becoming common. This has resulted in PCs replacing many other electronic gadgets (televisions, play stations, etc.), as people are inclined to use televisions and play stations in their PCs through software. Games are not an exception fro this electronic advancement. All this has increased the number of choices in computer games for the users. At the same time the quality of entertainment provided by these games has also decreased due to abundance of games in the market for PCs. On the other hand the task of ngame development for the developers is becoming tiresome, which requires scripting the game, modeling its contents and other such activities. Still it cannot be known how much the developed game is entertaining for the end users, as entertainment is a subjective term. Another issue from the point of view of game developers is the constant need of writing new games, requiring investment both in terms of time and resources.
In order to address afore mentioned challenges (measuring of entertainment and automated generation of games). First task is to devise some metrics that can quantify the entertainment value of a game. Although creating a single quantitative measure for all genres of games is not trivial, but a separate metrics for each can be devised. Based upon the entertainment metrics some computational intelligence techniques can be used to create new and entertaining games. In this work we create a set of metrics for measuring entertainment in computer games.The genres we address are board based games and video games (predator/prey and platform games). The metrics are based theories of entertainment in computer games, taken from literature. Further we use Evolutionary Algorithm (EA) to generate new and entertaining games using the proposed entertainment metrics as the fitness function. The EA starts with a randomly initialized set of population and using genetic operators (guided by the proposed entertainment metrics) we reach a final set of population that is optimized against entertainment. For the purpose of verifying the entertainment value of the evolved games with that of the human we conduct a human user survey and experiment using the controller learning ability.

Download Full Thesis
2,659 KB
S. No. Chapter Title of the Chapters Page Size (KB)
1 0 CONTENTS

 

iv
112 KB
2

1

INTRODUCTION

1.1 Motivation
1.2 Questions and Objective
1.3 Scientific Relevance
1.4 List of Publications
1.5 Thesis Outline
1.6 Summary

2
149 KB
3 2 BASICS OF INFORMATION HIDING AND DIGITAL WATERMARKING

2.1 Game
2.2 AI and Computer Games
2.3 Types of Computer Games
2.4 Tools and Techniques
2.5 Summary

11
626 KB
4 3 LITERATURE SURVEY

3.1 Board Based Games
3.2 Video Games
3.3 Physical Activating Games
3.4 Entertainment Theories
3.5 Summary

19
251 KB
5

4

ENTERTAINMENT METRICS

4.1 Board Based Games
4.2 Video Games (Predator/Prey and Platform)
4.3 Summary

35
322 KB
6

5

BOARD BASED GAMES

5.1 Search Space
5.2 Structure of the Chromosome
5.3 Software Agents for Playing the Games
5.4 Experiments
5.5 Analysis of Evolved Games
5.4 Learnability of Evolved Games
5.5 User Survey on Entertainment Value of Evolved Games
5.6 Hypothesis Testing
5.7 Metrics versus Metrics of Chess Checkers and the Evolved Games
5.8 Summary

47
574 KB
7

6

PREDATOR/PREY GAMES

6.1 Search Space
6.3 Chromosome Encoding
6.4 The Controller
6.5 Experimentation and Results
6.6 Verification of the results
6.7 Summary

75
733 KB
8

7

PLATFORM GAMES

7.1 Search Space
7.2 Chromosome Encoding
7.3 The Controller
7.4 Experimentation and Results
7.5 Verification of the results
7.6 Summary

98
248 KB
9

8

CONCLUSION

8.1 Answer to Problem Statements
8.2 Contributions
8.3 Limitations
8.4 Future Work
8.5 Summary

107
128 KB
10

9

REFERENCES AND APPENDIX

 

112
352 KB