This Article Full Text (PDF) All Versions of this Article: 1046878109335120v1 40/6/752    most recent References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Scopus Google Scholar Articles by Prakash, E. Articles by Wong, K.-W. Social Bookmarking                         What's this?

Advances in Games Technology: Software, Models, and Intelligence

Manchester Metropolitan University, Manchester, UK, e.prakash{at}mmu.ac.uk

Geoff Brindle

Manchester Metropolitan University, Manchester, UK, g.brindle{at}mmu.ac.uk

Kevin Jones

Nanyang Technological University, Singapore

Suiping Zhou

Nanyang Technological University, Singapore

Narendra S. Chaudhari

Nanyang Technological University, Singapore, asnarendra{at}ntu.edu.sg

Kok-Wai Wong

Murdoch University, Murdoch, Western Australia, Australia

Games technology has undergone tremendous development. In this article, the authors report the rapid advancement that has been observed in the way games software is being developed, as well as in the development of games content using game engines. One area that has gained special attention is modeling the game environment such as terrain and buildings. This article presents the continuous level of detail terrain modeling techniques that can help generate and render realistic terrain in real time. Deployment of characters in the environment is increasingly common. This requires strategies to map scalable behavior characteristics for characters as well. The authors present two important aspects of crowd simulation: the realism of the crowd behavior and the computational overhead involved. A good simulation of crowd behavior requires delicate balance between these aspects. The focus in this article is on human behavior representation for crowd simulation. To enhance the player experience, the authors present the concept of player adaptive entertainment computing, which provides a personalized experience for each individual when interacting with the game. The current state of game development involves using very small percentage (typically 4% to 12%) of CPU time for game artificial intelligence (AI). Future game AI requires developing computational strategies that have little involvement of CPU for online play, while using CPU’s idle capacity when the game is not being played, thereby emphasizing the construction of complex game AI models offline. A framework of such nonconventional game AI models is introduced.

Key Words: artificial intelligence • behavior modeling • board game • character modeling • conversational avatars • environment modeling • game AI • game development • game editor • game engine • game software • gardening game • genetic algorithms • hybrid soft computing • memetic algorithms • neural network optimization • programmable tournament • racing game • small world models • terrain modeling

This version was published on December 1, 2009

Simulation & Gaming, Vol. 40, No. 6, 752-801 (2009)
DOI: 10.1177/1046878109335120


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?