Institute of Information Theory and Automation

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Bibliography

Research Report

Fully probabilistic knowledge expression and incorporation

Kárný Miroslav, Andrýsek Josef, Bodini A., Guy Tatiana Valentine, Kracík Jan, Nedoma Petr, Ruggeri F.

: Istituto di Matematica Applicata e Tecnologie Informatiche, (Milano 2008)

: Research Report 8-10MI

: CEZ:AV0Z10750506

: 1M0572, GA MŠk, 2C06001, GA MŠk, GA102/08/0567, GA ČR

: Bayesian estimation, prior knowledge, automatised knowledge elicitation

: http://library.utia.cas.cz/separaty/2008/AS/karny-fully probabilistic knowledge expression and incorporation.pdf

(eng): Exploitation of prior knowledge in parameter estimation is vital whenever data is not informative enough. Elicitation and quantification of prior knowledge is a well-elaborated art in social and medical appliations but not in engineering ones. Frequently required involvment of a facilitator is mostly unrealistic due to either facilitators' high costs or the high complexitu of modelled relationships that cannot be grasped by the human. This paper provides a facilitator-free approach exploiting a methodology of knowledge sharing. The considered task assumes prospective models be indexed by an unknown finite-dimensional parameter. The parameter is estimated using (i) observed data; (ii) a prior probability density function (pdf); and (iii) uncertain expert's information on the modelled data. The parametric model specifies pdf of the system's output conditioned on realised data and parameter.

: BB

2019-01-07 08:39