Creating a multi-purpose first person shooter bot with reinforcement learning

McPartland, M. and Gallagher, M. (2008). Creating a multi-purpose first person shooter bot with reinforcement learning. In: P. Hingston and L. Barone, Computational Intelligence and Games 2008. IEEE Symposium on Computational Intelligence and Games 2008 (CIG '08), Perth, Australia, (143-150). 15-18 December 2008. doi:10.1109/CIG.2008.5035633

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Author McPartland, M.
Gallagher, M.
Title of paper Creating a multi-purpose first person shooter bot with reinforcement learning
Conference name IEEE Symposium on Computational Intelligence and Games 2008 (CIG '08)
Conference location Perth, Australia
Conference dates 15-18 December 2008
Proceedings title Computational Intelligence and Games 2008
Journal name 2008 Ieee Symposium On Computational Intelligence and Games
Place of Publication Piscataway, NJ, U.S.A.
Publisher IEEE
Publication Year 2008
Sub-type Fully published paper
DOI 10.1109/CIG.2008.5035633
ISBN 978-1-4244-2973-8
Editor P. Hingston
L. Barone
Start page 143
End page 150
Total pages 8
Language eng
Abstract/Summary Reinforcement learning is well suited to first person shooter bot artificial intelligence as it has the potential to create diverse behaviors without the need to implicitly code them. This paper compares three different reinforcement learning approaches to create a bot with a universal behavior set. Results show that using a hierarchical or rule based approach, combined with reinforcement learning, is a promising solution to creating first person shooter bots that offer a rich and diverse behavior set.
Subjects E1
890203 Computer Gaming Software
080199 Artificial Intelligence and Image Processing not elsewhere classified
Keyword Computer games
Learning
Q-Index Code E1
Q-Index Status Confirmed Code

 
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Created: Sat, 18 Apr 2009, 00:43:34 EST by Donna Clark on behalf of School of Information Technol and Elec Engineering