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Fundamenta Informaticae is an international journal publishing original research results in all areas of theoretical computer science. Papers are encouraged contributing:
- solutions by mathematical methods of problems emerging in computer science
- solutions of mathematical problems inspired by computer science.
Topics of interest include (but are not restricted to): theory of computing, complexity theory, algorithms and data structures, computational aspects of combinatorics and graph theory, programming language theory, theoretical aspects of programming languages, computer-aided verification, computer science logic, database theory, logic programming, automated deduction, formal languages and automata theory, concurrency and distributed computing, cryptography and security, theoretical issues in artificial intelligence, machine learning, pattern recognition, algorithmic game theory, bioinformatics and computational biology, quantum computing, probabilistic methods, & algebraic and categorical methods.
Article Type: Research Article
Abstract: The paper presents the process of taking global decisions on the basis of the knowledge of local decision systems involving the mutually complementary observations of objects which can be mutually contradictory. The authors suggest the organization of local decision systems into a multi-agent system with a hierarchical structure. The structure of multi-agent systems and the theoretical aspects of the organization of the system are presented. A density-based algorithm has been used in the process of taking global decisions. Furthermore the paper presents the results of experiments conducted using realistic data.
Keywords: decision system, multi-agent system, global decision, density-based algorithm
Citation: Fundamenta Informaticae, vol. 101, no. 1-2, pp. 125-141, 2010
Authors: Wolski, Marcin
Article Type: Research Article
Abstract: The paper aims to establish topological links between perception of objects (as it is defined in the framework of near sets) and classification of these objects (as it is defined in the framework of rough sets). In the near set approach, the discovery of near sets (i.e. sets containing objects with similar descriptions) starts with the selection of probe functions which provide a basis for describing and discerning objects. On the other hand, in the rough set approach, the classification of objects is based on object attributes which are collected into information systems (or data tables). As is well-known, an …information system can be represented as a topological space (U, τE ). If we pass froman approximation space (U,E) to the quotient space U/E, where points represent indiscernible objects of U, then U/E will be endowed with the discrete topology induced (via the canonical projection) by τE . The main objective of this paper is to show how probe functions can provide new topologies on the quotient set U/E and, in consequence, new (perceptual) topologies on U. Show more
Citation: Fundamenta Informaticae, vol. 101, no. 1-2, pp. 143-155, 2010
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