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Decision-Theoretic Throttling for Optimisitc Simulations of Multi-Agent Systems Michael Lees, Brian Logan, School of Computer Science and Information Technology University of Nottingham, UK {mhl,bsl}@cs.nott.ac.uk Chen D
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Document Date: 2006-12-28 11:41:25


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San Diego / Paris / /

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IEEE Computer Society Press / High Autonomy Systems / ACM Press / /

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Information Technology University of Nottingham / University of Maryland / Computer Science University of Birmingham / /

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large-grain multi-agent systems / expected utilities / multi-agent systems / closed queueing systems / event systems / probabilistic protocol / decision theoretic algorithm / probabilistic distributed simulation protocol / virtual and real time components / /

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School of Computer Science / Congress / Society for Modelling and Simulation International / Computer Science and Information Technology University of Nottingham / Ton Oguara and Georgios Theodoropoulos School / University of Maryland / National Bureau of Standards / European Union / University of Birmingham / /

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Michael Lees / Brian Logan / Chen Dan / /

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agent designer / editor / researcher / representative / /

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t10 / RAM / iRiver T30 Portable Audio Device / /

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C++ / /

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Maryland / California / /

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Communications of the ACM / /

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Moving Time Windows protocol / RAM / decision theoretic algorithm / load balancing / probabilistic distributed simulation protocol / artificial intelligence / Chiola protocol / simulation system / simulation / intelligent agent / probabilistic protocol / gigabit Ethernet / tested using a simulation / /

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