2010
DOI: 10.1007/978-3-642-11479-3_5
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Satisfiability Judgement under Incomplete Information

Abstract: Abstract. In this paper we keep on discussing satisfiability of conditions by objects when information about the situation considered, including objects of some sort and concepts comprised of them, is incomplete. Our approach to satisfiability is that of concept modelling and we have a rough granular view on the problem. Objects considered are known partially, in terms of values of attributes of Pawlak information systems. An additional knowledge (domain knowledge) is assumed to be available. We choose descrip… Show more

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Cited by 3 publications
(2 citation statements)
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References 85 publications
(127 reference statements)
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“…Such a form of rule applicability, called rough applicability, is based on various kinds of rough satisfiability of sets of rule premises, where granulation of information plays an important role. Gomolinska (2010) has presented the rough granular view on the problem of satisfiability of formulas (defining some conditions) by objects under incomplete information about the objects and the situation. Judgement of formula satisfiability is important, e.g., when making the decision whether or not to apply a rule to an object.…”
Section: Introductionmentioning
confidence: 99%
“…Such a form of rule applicability, called rough applicability, is based on various kinds of rough satisfiability of sets of rule premises, where granulation of information plays an important role. Gomolinska (2010) has presented the rough granular view on the problem of satisfiability of formulas (defining some conditions) by objects under incomplete information about the objects and the situation. Judgement of formula satisfiability is important, e.g., when making the decision whether or not to apply a rule to an object.…”
Section: Introductionmentioning
confidence: 99%
“…In AI, specification of speech acts is closely related to dynamical character of systems in which dialogues are performed. Thereby, participants of dialogues decide which speech acts use based on reasoning about changes, often under incomplete information (see Skowron et al 2012, Gomolinska 2010 for rough set and Kacprzak et al 2013 for fuzzy view on this problem).…”
mentioning
confidence: 99%