DocumentCode
2416039
Title
Interactively training first person shooter bots
Author
McPartland, Michelle ; Gallagher, Marcus
Author_Institution
Univ. of Queensland, Brisbane, QLD, Australia
fYear
2012
fDate
11-14 Sept. 2012
Firstpage
132
Lastpage
138
Abstract
Interactive training is a technique that allows humans to guide a learning algorithm. This technique is well suited to training first person shooter bots as it allows game designers to iterate a range of behaviors in real-time. This paper investigates an initial attempt at allowing users to interact with the learning process of a reinforcement learning algorithm to create first person shooter bot behaviors. The results clearly show that it is possible to create different types of bot behaviors using the developed interactive training tool.
Keywords
computer games; interactive systems; learning (artificial intelligence); software agents; first person shooter bot behaviors; first person shooter bots; interactive training tool; reinforcement learning algorithm; Games; Humans; Learning systems; Machine learning; Training; Weapons;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Games (CIG), 2012 IEEE Conference on
Conference_Location
Granada
Print_ISBN
978-1-4673-1193-9
Electronic_ISBN
978-1-4673-1192-2
Type
conf
DOI
10.1109/CIG.2012.6374149
Filename
6374149
Link To Document