QUT ePrints

A game theory approach to high-level strategic planning in first person shooters

Rasmussen, Rune K. (2008) A game theory approach to high-level strategic planning in first person shooters. In The 5th Australasian Conference on Interactive Entertainment, 3-4 December 2008, Queensland University of Technology, Brisbane.

[img] Published Version (PDF 434kB)
Administrators only | Request a copy from author

View at publisher

Abstract

As computer systems become more dependent on standalone devices such as graphics cards, video game developers can execute additional features on the CPU; high-level AI in video games is one such feature. The problem of developing high quality AI for video games is not simple, as human and computer interactions can be very complex. An exception can be found in the classical board game genre, which involves well dened games and players who apply rational policies to win. Many artificial board-game players can make moves within set time limits and are able to play at expert levels. Given that high-quality AI technologies already exist for many board games, this paper explores the question: how can the technologies used in articial board game players be applied to high-level strategic planning in First Person Shooters?

Impact and interest:

0 citations in Scopus
Search Google Scholar™

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 20883
Item Type: Conference Paper
Additional URLs:
Keywords: Algorithms, Design, Theory
DOI: 10.1145/1514402.1514409
ISBN: 9781605584249
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Expert Systems (080105)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Simulation and Modelling (080110)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2008 Association for Computing Machinery
Deposited On: 02 Jun 2009 14:46
Last Modified: 01 Mar 2012 00:13

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page