Original title: Supra-Bayesian Approach to Merging of Incomplete and Incompatible Data
Authors: Sečkárová, Vladimíra
Document type: Papers
Conference/Event: 24th Annual Conference on Neural Information Processing Systems, Whistler, B.C. Canada (CA), 2010-12-06 / 2010-12-11
Year: 2010
Language: eng
Abstract: In practice we often need to take every available information into account. Unfortunately the pieces of information given by different sources are often incomplete (with respect to what we are interested in) and have different forms. In this work we try to solve the problem of treating such data in order to get an optimal merger of them. We present a systematic and unified way how to combine the pieces of information by using a Supra-Bayesian approach and other mathematical tools, e.g. Kerridge inaccuracy, maximum entropy principle. To show how the proposed method works a simple example is given at the end of the work.
Keywords: Bayesian decision making; sharing of probabilistic information; Supra-Bayesian approach
Project no.: CEZ:AV0Z10750506 (CEP), GA102/08/0567 (CEP), 1M0572 (CEP)
Funding provider: GA ČR, GA MŠk
Host item entry: Decision Making with Multiple Imperfect Decision Makers, ISBN 978-80-903834-5-6

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2010/AS/seckarova-supra-bayesian approach to merging of incomplete and incompatible data.pdf
Original record: http://hdl.handle.net/11104/0191792

Permalink: http://www.nusl.cz/ntk/nusl-42193


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Research > Institutes ASCR > Institute of Information Theory and Automation
Conference materials > Papers