Original title: On Structure of Predictors Allowing Distributed Dynamic Bayesian Decision-Making
Translated title: O strukturách prediktorů umožňujících distribuované dynamické Bayesovské rozhodování
Authors: Šmídl, Václav
Document type: Research reports
Year: 2007
Language: eng
Series: Research Report, volume: 2211
Abstract: [eng] [cze]
Decentralized adaptive control is based on the use of many local controllers in parallel, each of them estimating its own local model and pursuing its local aims. If each controller designs its strategy using only its own model, the resulting control may be poor since consequences of actions of the neighbors are not taken into account. We seek a way how to improve algorithm of decision strategy design of a single local controller without significant increase in complexity of the local model or complexity of the design procedure. In this paper we study variants of distributed dynamic programming that could be evaluated locally. Specifically, we will investigate variants of the fully probabilistic control strategy design. Distributed and cen- tralized control strategies will be compared. Distribuované adaptivní řízení spočívá v paralelním běhu několika adaptivních regulátorů, z nichž každý odhaduje svůj model a navrhuje valstní strategii řízení. Pokud by takový regulátor nevzal do úvahy přítomnost ostatních regulátorů, může dojít k nežádoucímu chování. V této práci se zabýváme Bayesovským přístupem k problému. Cílem je zjistit jaká struktura centralizovaného prediktoru umožňuje návrh distribuované strategie.
Keywords: Bayesian decision-making; decentralized adaptive control; distributed control; dynamic programming
Project no.: CEZ:AV0Z10750506 (CEP), 1M0572 (CEP), 1ET100750401 (CEP)
Funding provider: GA MŠk, GA AV ČR

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at the institute of the Academy of Sciences.
Original record: http://hdl.handle.net/11104/0161108

Permalink: http://www.nusl.cz/ntk/nusl-38843


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Research > Institutes ASCR > Institute of Information Theory and Automation
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