Reading the play : adaptation by prediction of agent motion
Contribuinte(s) |
Kim, Jonghyuk Mahony, Robert |
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Data(s) |
2008
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Resumo |
An adaptive agent improves its performance by learning from experience. This paper describes an approach to adaptation based on modelling dynamic elements of the environment in order to make predictions of likely future state. This approach is akin to an elite sports player being able to “read the play”, allowing for decisions to be made based on predictions of likely future outcomes. Modelling of the agent‟s likely future state is performed using Markov Chains and a technique called “Motion and Occupancy Grids”. The experiments in this paper compare the performance of the planning system with and without the use of this predictive model. The results of the study demonstrate a surprising decrease in performance when using the predictions of agent occupancy. The results are derived from statistical analysis of the agent‟s performance in a high fidelity simulation of a world leading real robot soccer team. |
Formato |
application/pdf |
Identificador | |
Publicador |
Australian Robotics and Automation Association Inc |
Relação |
http://eprints.qut.edu.au/32853/1/c32853.pdf http://www.araa.asn.au/acra/acra2008/ Ball, David & Wyeth, Gordon (2008) Reading the play : adaptation by prediction of agent motion. In Kim, Jonghyuk & Mahony, Robert (Eds.) Proceedings of Australasian Conference on Robotics and Automation 2008, Australian Robotics and Automation Association Inc, Canberra. |
Direitos |
Copyright 2008 [please consult the authors] |
Fonte |
Faculty of Built Environment and Engineering; Institute for Future Environments; Science & Engineering Faculty |
Palavras-Chave | #080101 Adaptive Agents and Intelligent Robotics |
Tipo |
Conference Paper |