Classifying an opponent's behaviour in robot soccer

Ball, D. M. and Wyeth, G. F. (2003). Classifying an opponent's behaviour in robot soccer. In: J. Roberts and G. Wyeth, Proceedings of the 2003 Australasian Conference on Robotics and Automation. Australasian Conference on Robotics and Automation 2003, Brisbane, Australia, (1-8). 1-3 December 2003.


Author Ball, D. M.
Wyeth, G. F.
Title of paper Classifying an opponent's behaviour in robot soccer
Conference name Australasian Conference on Robotics and Automation 2003
Conference location Brisbane, Australia
Conference dates 1-3 December 2003
Proceedings title Proceedings of the 2003 Australasian Conference on Robotics and Automation
Place of Publication Brisbane, Australia
Publisher Australian Robotics and Automation Association (ARAA)
Publication Year 2003
Sub-type Fully published paper
ISBN 0-9587583-5-2
Editor J. Roberts
G. Wyeth
Start page 1
End page 8
Total pages 8
Collection year 2003
Language eng
Abstract/Summary This paper illustrates the prediction of opponent behaviour in a competitive, highly dynamic, multi-agent and partially observableenvironment, namely RoboCup small size league robot soccer. The performance is illustrated in the context of the highly successful robot soccer team, the RoboRoos. The project is broken into three tasks; classification of behaviours, modelling and prediction of behaviours and integration of the predictions into the existing planning system. A probabilistic approach is taken to dealing with the uncertainty in the observations and with representing the uncertainty in the prediction of the behaviours. Results are shown for a classification system using a Naïve Bayesian Network that determines the opponent’s current behaviour. These results are compared to an expert designed fuzzy behaviour classification system. The paper illustrates how the modelling system will use the information from behaviour classification to produce probability distributions that model the manner with which the opponents perform their behaviours. These probability distributions are show to match well with the existing multi-agent planning system (MAPS) that forms the core of the RoboRoos system.
Subjects E1
380305 Knowledge Representation and Machine Learning
780199 Other
Keyword Opponent behaviour
Robot soccer
Q-Index Code E1

 
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Created: Fri, 24 Aug 2007, 10:18:55 EST