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Variational Bayes in Distributed Fully Probabilistic Decision Making
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SYSNO ASEP 0368318 Druh ASEP C - Konferenční příspěvek (mezinárodní konf.) Zařazení RIV D - Článek ve sborníku Název Variational Bayes in Distributed Fully Probabilistic Decision Making Tvůrce(i) Šmídl, Václav (UTIA-B) RID, ORCID
Tichý, Ondřej (UTIA-B) RID, ORCIDCelkový počet autorů 2 Zdroj.dok. The 2nd International Workshop od Decision Making with Multiple Imperfect Decision Makers. Held in Conjunction with the 25th Annual Conference on Neural Information Processing Systems (NIPS 2011). - Prague : Institute of Information Theory and Automation, 2011 - ISBN 978-80-903834-6-3 Rozsah stran s. 73-80 Poč.str. 8 s. Akce The 2nd International Workshop od Decision Making with Multiple Imperfect Decision Makers. Held in Conjunction with the 25th Annual Conference on Neural Information Processing Systems (NIPS 2011) Datum konání 16.12.2011-16.12.2011 Místo konání Sierra Nevada Země ES - Španělsko Typ akce WRD Jazyk dok. eng - angličtina Země vyd. CZ - Česká republika Klíč. slova Fully Probabilistic Design ; Variational Bayes method ; distributed control Vědní obor RIV BB - Aplikovaná statistika, operační výzkum CEP 1M0572 GA MŠMT - Ministerstvo školství, mládeže a tělovýchovy TA01030603 GA TA ČR - Technologická agentura ČR CEZ AV0Z10750506 - UTIA-B (2005-2011) Anotace We are concerned with design of decentralized control strategy for stochastic systems with global performance measure. It is possible to design optimal centralized control strategy, which often cannot be used in distributed way. The distributed strategy then has to be suboptimal (imperfect) in some sense. In this paper, we propose to optimize the centralized control strategy under the restriction of conditional independence of control inputs of distinct decision makers. Under this optimization, the main theorem for the Fully Probabilistic Design is closely related to that of the well known Variational Bayes estimation method. The resulting algorithm then requires communication between individual decision makers in the form of functions expressing moments of conditional probability densities. This contrasts to the classical Variational Bayes method where the moments are typically numerical. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2012
Počet záznamů: 1