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An interactive game-design assistant
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International Conference on Intelligent User Interfaces archive
Proceedings of the 13th international conference on Intelligent user interfaces table of contents
Gran Canaria, Spain
SESSION: Visualization table of contents
Pages 90-98  
Year of Publication: 2008
ISBN:978-1-59593-987-6
Authors
Mark J. Nelson  Georgia Institute of Technology
Michael Mateas  University of California, Santa Cruz
Sponsors
SIGART: ACM Special Interest Group on Artificial Intelligence
AAAI : Association for the Advancement of Artifical Intelligence
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Game-design novices increasingly hope to use game-like expression as a way to express content such as opinions and educational material. Existing game-design toolkits such as Game Maker ease the programming burden, bringing the design of small games within the technical reach of low-budget, non-expert groups. The design process itself remains a roadblock, however: It is not at all obvious how to present topics such as political viewpoints or bike safety in a way that makes use of the unique qualities of the interactive game medium. There are no tools to assist in that aspect of the game design process, and as a result virtually all expressive games come from a small number of game studios founded by experts in designing such games. We propose a game-design assistant that acts in a mixed-initiative fashion, helping the author understand the content of her design-in-progress, providing suggestions or automating the process where possible, and even offering the possibility for parts of the game to be dynamically generated at runtime in response to player interaction. We describe a prototype system that interactively helps authors define spaces of games in terms of common-sense constraints on their real-world references, provides support for them to understand and iteratively refine such spaces, and realizes specific games from the spaces as playable mobile-phone games in response to user input.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
D. Andre and S. Russell. Programming reinforcement learning agents. In Advances in Neural Information Processing Systems (NIPS), 2000.
 
3
S. Bhat, C. L. Isbell, Jr., and M. Mateas. On the difficulty of modular reinforcement learning for real-world partial programming. In Proceedings of the 21st National Conference on Artificial Intelligence (AAAI), 2006.
 
4
5
 
6
 
7
C. Fellbaum, editor. WordNet: An Electronic Lexical Database. MIT Press, 1998.
 
8
G. Frasca. Play the Message: Play, Game and Videogame Rhetoric. PhD thesis, IT University of Copenhagen, 2007.
 
9
Y. Gil and J. Kim. Interactive knowledge acquisition tools: A tutoring perspective. In Proceedings of the 24th Annual Conference of the Cognitive Science Society, 2002.
 
10
C. Gingold. What WarioWare can teach us about game design. Game Studies, 5(1), 2005.
11
 
12
H. Lieberman, H. Liu, P. Singh, and B. Barry. Beating common sense into interactive applications. AI Magazine, 25(4):63--76, 2004.
 
13
 
14
M. Mateas. Expressive AI: A hybrid art and science practice. Leonardo, 34(2):147--153, 2001.
 
15
M. Mateas. Procedural literacy: Educating the new media practitioner. On the Horizon, 13(1), 2005.
 
16
E. T. Mueller. Natural Language Processing with ThoughtTreasure. Signiform, 1998. Online: http://www.signiform.com/tt/book/.
 
17
M. J. Nelson and M. Mateas. Towards automated game design. In AI*IA 2007: Artificial Intelligence and Human-Oriented Computing, pages 626--637. Springer, 2007. Lecture Notes in Computer Science 4733.
 
18
 
19
R. Ovans and R. Davison. An interactive constraint-based expert assistant for music composition. In Proceedings of the 9th Canadian Conference on Artificial Intelligence, 1992.
 
20
B. Pell. Metagame in symmetric, chess-like games. In L. V. Allis and H. J. van den Herik, editors, Heuristic Programming in Artificial Intelligence 3: The Third Computer Olympiad. Ellis Horwood, 1992.
 
21
E. Rosch. Natural categories. Cognitive Psychology, 4:328--350, 1973.
 
22
P. Singh. The public acquisition of commonsense knowledge. In Proceedings of the AAAI Spring Symposium on Acquiring (and Using) Linguistic (and World) Knowledge for Information Access, 2002.
23


Collaborative Colleagues:
Mark J. Nelson: colleagues
Michael Mateas: colleagues