Classifying an opponent’s behaviour in robot soccer
Ball, David & Wyeth, Gordon (2003) Classifying an opponent’s behaviour in robot soccer. In Roberts, Jonathan & Wyeth, Gordon (Eds.) Proceedings of the Australasian Conference on Robotics and Automation, 2003, Australian Robotics and Automation Association Inc, Brisbane, Queensland.
This paper illustrates the prediction of opponent behaviour in a competitive, highly dynamic, multi-agent and partially observable environment, 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.
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|Item Type:||Conference Paper|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)|
|Copyright Owner:||Copyright 2003 [please consult the authors]|
|Deposited On:||23 Jun 2010 00:05|
|Last Modified:||10 Aug 2011 13:07|
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