Full Text:
<3519>
CLC number: G89
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2009-02-16
Cited: 6
Clicked: 5749
Human-centered modeling for style-based adaptive games
| |||||||||||||
Chee-onn WONG, Jongin KIM, Eunjung HAN, Keechul JUNG. Human-centered modeling for style-based adaptive games[J]. Journal of Zhejiang University Science A, 2009, 10(4): 530-534.
@article{title="Human-centered modeling for style-based adaptive games",
author="Chee-onn WONG, Jongin KIM, Eunjung HAN, Keechul JUNG",
journal="Journal of Zhejiang University Science A",
volume="10",
number="4",
pages="530-534",
year="2009",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A0820593"
}
%0 Journal Article
%T Human-centered modeling for style-based adaptive games
%A Chee-onn WONG
%A Jongin KIM
%A Eunjung HAN
%A Keechul JUNG
%J Journal of Zhejiang University SCIENCE A
%V 10
%N 4
%P 530-534
%@ 1673-565X
%D 2009
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A0820593
TY - JOUR
T1 - Human-centered modeling for style-based adaptive games
A1 - Chee-onn WONG
A1 - Jongin KIM
A1 - Eunjung HAN
A1 - Keechul JUNG
J0 - Journal of Zhejiang University Science A
VL - 10
IS - 4
SP - 530
EP - 534
%@ 1673-565X
Y1 - 2009
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A0820593
Abstract: This letter proposes a categorization matrix to analyze the playing style of a computer game player for a shooting game genre. Our aim is to use human-centered modeling as a strategy for adaptive games based on entertainment measure to evaluate the playing experience. We utilized a self-organizing map (SOM) to cluster the player’s style with the data obtained while playing the game. We further argued that style-based adaptation contributes to higher enjoyment, and this is reflected in our experiment using a supervised multilayered perceptron (MLP) network.
[1] Bartle, R., 1996. Hearts, Clubs, Diamonds, Spades: Players Who Suit MUDS. Http://www.mud.co.uk/richard/hcds.htm
[2] Charles, D., Black, M., 2004. Dynamic Player Modeling: a Framework for Player-centered Digital Games. Int. Conf. on Computer Games: Artificial Intelligence, Design and Education, p.29-35.
[3] Charles, D., McNeill, M., McAlister, M., Black, M., Moore, A., Stringer, K., Kucklich, J., Kerr, A., 2005. Player-centered Design: Player Modeling and Adaptive Digital Games. Proc. DiGRA Conf.: Changing Views—World in Play, p.285-298.
[4] Clarke, D., Duimering, P.R., 2006. How computer gamers experience the game situation: a behavioral study. ACM Comput. Entertain., 4(3):Article 6.
[5] Houlette, R., 2003. Player Modeling for Adaptive Games. AI Game Programming Wisdom II, Charles River Media, p.557-566.
[6] Kerr, A., Kucklich, J., Brereton, P., 2006. New media—new pleasures Int. J. Cult. Stud., 9(1):63-82.
[7] Malone, T.W., 1981. What makes computer games fun? Byte, 6:258-277.
[8] Pantic, M., Pentland, A., Nijholt, A., Huang, T., 2006. Human Computing and Machine Understanding of Human Behavior: A Survey. 8th Int. Conf. on Multimodal Interfaces, p.239-248.
[9] Salen, K., Zimmerman, E., 2003. Rules of Play: Game Design Fundamentals. MIT Press, Cambridge, MA.
[10] Spronck, P., Ponsen, M., Sprinkhuizen-Kyuper, I., Postma, E., 2006. Adaptive game AI with dynamic scripting. Machine Learning, 63(3):217-248.
[11] Thurau, C., Bauchage, C., Sagerer, G., 2004. Imitation Learning at All Levels of Game AI. Proc. Int. Conf. on Computer Games, Artificial Intelligence, Design and Education, p.402-408.
[12] Togelius, J., Nardi, R.D., Lucas, S.M., 2007. Towards Automatic Personalized Content Creation for Racing Games. IEEE Symp. on Computational Intelligence and Games, p.252-259.
[13] Yannakakis, G.N., Hallam, J., 2007. Game and Player Feature Selection for Entertainment Capture. IEEE Symp. on Computational Intelligence and Games, p.244-251.
Open peer comments: Debate/Discuss/Question/Opinion
<1>