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1

Finite-valued Logics for Information Processing

Avron A., Konikowska B.

Fundamenta Informaticae

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2012

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Vol. 114, nr 1

1-30

EN

We examine the issue of collecting and processing information from various sources, which involves handling incomplete and inconsistent information. Inspired by the framework first proposed by Belnap, we consider structures consisting of information sources which provide information about the values of formulas of classical propositional logic, and a processor which collects that information and extends it by deriving conclusions following from it according to the truth tables of classical logic, applied forward and backward. Our model extends Belnap’s in allowing the sources to provide information also about complex formulas. As that framework cannot be captured using finite ordinary logical matrices, if we want to represent each of the relevant logics with a single matrix, we employ Nmatrices for that purpose. In opposition to the approach proposed in our earlier work, we assume that the information sources are reasonable, i.e. that they provide information consistent with certain coherence rules. We provide sound and complete sequent calculi admitting strong cut elimination for the logic of a single information source, and (several variants of) the logic generated by the source and processor structures described above. In doing this, we also provide new characterizations for some known logics. We prove that, in opposition to the variantwith unconstrained information sources considered earlier, the latter logic cannot be generated by structures with any bounded number of sources.

2

Monadic Algebras: a Standpoint on Rough Sets

Wolski M.

Fundamenta Informaticae

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2011

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Vol. 108, nr 3/4

181-196

EN

The paper studies complete and incomplete information systems, i.e. basic structures of rough set theory (RST), from the standpoint of monadic Boolean algebras (MBAs). In the first part we recall a simple characterisation of RST as a theory of MBAs. In the second part the paper discusses approximation operators obtained from incomplete information systems. In this case we lose a direct link to MBAs and thus our aim is to obtain an MBA which will additionally be interesting from the perspective of RST. In the third part we consider a simple application of approximation operators based on this MBA.

3

An Investigation About Rough Set Theory: Some Foundational and Mathematical Aspects

Cattaneo G.

Fundamenta Informaticae

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2011

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Vol. 108, nr 3/4

197-221

EN

The approach to rough set theory is investigated from the foundational point of view, starting from the formal analysis of the mathematical structures generated by equivalence relations (the standard Pawlak approach to complete information systems) and then by tolerance or similarity relations (the approach to roughness by incomplete information systems). Making use of these approaches the “minimal” meta–theoretical principles which allow one to treat approximations in rough set theory are discussed and formulated in explicit way, in particular the conditions which can assure what can be rightly considered as lower and upper approximations of some approximable set. The hierarchy of approximation spaces generated in this way on a universe is then discussed.

4

Flexible Indiscernibility Relations for Missing Attribute Values

Latkowski R.

Fundamenta Informaticae

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2005

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Vol. 67, nr 1-3

131--147

EN

The indiscernibility relation is a fundamental concept of the rough set theory. The original definition of the indiscernibility relation does not capture the situation where some of the attribute values are missing. This paper tries to enhance former works by proposing an individual treatment of missing values at the attribute or value level. The main assumption of the theses presented in this paper considers that not all missing values are semantically equal. We propose two different approaches to create an individual indiscernibility relation for a particular information system. The first relation assumes variable, but fixed semantics of missing attribute values in different columns. The second relation assumes different semantics of missing attribute values, although this variability is limited with expressive power of formulas utilizing descriptors. We provide also a comparison of flexible indiscernibility relations and missing value imputation methods. Finally we present a simple algorithm for inducing sub-optimal relations from data.