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 :
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