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Merging 'Reasoning' and Filtering in a Bayesian Framework: Some Sensitivity and Optimality Aspects
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1989 (English)In: Proceedings of the 28th Conference on Decision and Control, 1989, 1427-1429 p.Conference paper, Published paper (Refereed)
Abstract [en]

It is shown how to incorporate symbolic or logical knowledge into a conventional framework of noisy observations in dynamical systems. The idea is based on approximating the optimal solution that could, theoretically, be computed if a complete Bayesian framework were known (and infinite computational power were available). The nature of the approximations, the deviations from optimality and the sensitivity to ad hoc parameters are specifically addressed.

Place, publisher, year, edition, pages
1989. 1427-1429 p.
Keyword [en]
Bayes methods, Filtering and prediction theory, Inference mechanisms, Knowledge representation
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-100545DOI: 10.1109/CDC.1989.70377OAI: oai:DiVA.org:liu-100545DiVA: diva2:663063
Conference
28th Conference on Decision and Control, 13-15 December, 1989, Tampa, FL, USA
Available from: 2013-11-09 Created: 2013-11-09 Last updated: 2014-02-06

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Ljung, LennartMillnert, Mille

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