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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F03%3A03093568%21RIV%2F2004%2FMSM%2F212304%2FN
rdf:type
n4:Vysledek skos:Concept
dcterms:description
This paper discusses experiences and perspectives of utilisation of declarative knowledge structures as a convenient knowledge base medium in configuration expert systems. Although many successful systems have been developed, these are often difficult to maintain and to generalize in rapidly changing domains. In this paper we address the problem of building intelligent knowledge based systems with emphasis on their maintainability. Firstly, several industrial applications of proof planning, a theorem proving technique, will be described and their advantages and flaws will be discussed. This discussion is followed by the theoretical foundation of decision planning knowledge representation framework that, based on proof planning, facilitates separate administration of inference problem solving knowledge and the domain theory axioms. Machine learning methods for maintaining the inference knowledge to be up-to-date with permanently changing domain theory are commented and evaluated. This paper discusses experiences and perspectives of utilisation of declarative knowledge structures as a convenient knowledge base medium in configuration expert systems. Although many successful systems have been developed, these are often difficult to maintain and to generalize in rapidly changing domains. In this paper we address the problem of building intelligent knowledge based systems with emphasis on their maintainability. Firstly, several industrial applications of proof planning, a theorem proving technique, will be described and their advantages and flaws will be discussed. This discussion is followed by the theoretical foundation of decision planning knowledge representation framework that, based on proof planning, facilitates separate administration of inference problem solving knowledge and the domain theory axioms. Machine learning methods for maintaining the inference knowledge to be up-to-date with permanently changing domain theory are commented and evaluated.
dcterms:title
Decision planning knowledge representation framework: A case-study Decision planning knowledge representation framework: A case-study
skos:prefLabel
Decision planning knowledge representation framework: A case-study Decision planning knowledge representation framework: A case-study
skos:notation
RIV/68407700:21230/03:03093568!RIV/2004/MSM/212304/N
n5:strany
147 ; 174
n5:aktivita
n6:Z
n5:aktivity
Z(MSM 212300013)
n5:cisloPeriodika
1-2
n5:dodaniDat
n11:2004
n5:domaciTvurceVysledku
n14:2490013
n5:druhVysledku
n16:J
n5:duvernostUdaju
n12:S
n5:entitaPredkladatele
n8:predkladatel
n5:idSjednocenehoVysledku
602857
n5:idVysledku
RIV/68407700:21230/03:03093568
n5:jazykVysledku
n18:eng
n5:klicovaSlova
expert systems;industrial configuration;machine learning;multi-agent systems;theorem proving
n5:klicoveSlovo
n7:expert%20systems n7:multi-agent%20systems n7:industrial%20configuration n7:theorem%20proving n7:machine%20learning
n5:kodStatuVydavatele
NL - Nizozemsko
n5:kontrolniKodProRIV
[F7AD1EC91F3D]
n5:nazevZdroje
Annals of Mathematics and Artificial Intelligence
n5:obor
n15:JC
n5:pocetDomacichTvurcuVysledku
1
n5:pocetTvurcuVysledku
1
n5:rokUplatneniVysledku
n11:2003
n5:svazekPeriodika
39
n5:tvurceVysledku
Pěchouček, Michal
n5:zamer
n10:MSM%20212300013
s:issn
1012-2443
s:numberOfPages
28
n13:organizacniJednotka
21230