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Linking Reaction Systems with Rough Sets

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Języki publikacji
EN
Abstrakty
EN
Reaction system is a model of interactive computations which was motivated by the functioning of the living cell. It is an idealized mathematical model, also because it abstracts from the complex nature of the physical systems where only partial, incomplete information is available (e.g., about their states). The framework of rough sets was developed to deal with such incomplete information. In this paper we establish a connection between reaction systems and rough sets. This is done in a somewhat broader perspective of the relationship between “pure” mathematical models and “realistic models” that take into account the limitation of perceiving physical reality.
Wydawca
Rocznik
Strony
283--302
Opis fizyczny
Bibliogr. 25 poz., rys.
Twórcy
autor
  • Department of Mathematics and Informatics, University of Warmia and Mazury, Olsztyn, Słoneczna 54, 10-710 Olsztyn, Poland
  • Leiden Institute of Advanced Computer Science, Leiden University, P.O. Box 9512, NL-2300 RA Leiden, The Netherlands
  • The Dziubanski Foundation of Knowledge Technology, Nowogrodzka 31, 00-511 Warsaw, Poland
  • Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland
Bibliografia
  • [1] Barwise J, Seligman J. Information Flow: The Logic of Distributed Systems. Cambridge Tracts in Theoretical Computer Science, Cambridge University Press, Cambridge, UK, 1997. ISBN-13:978-0521070997, 10:0521070996.
  • [2] Brijder R, Ehrenfeucht A, Main MG, Rozenberg G. A tour of reaction systems. International Journal of Foundations of Computer Science. 2011;22(7):1499-1517. URL https://doi.org/10.1142/S0129054111008842.
  • [3] Brooks FP. The Mythical Man-Month: Essays on Software Engineering. Addison-Wesley, Boston, 1975. (extended Anniversary Edition in 1995). ISBN-10:9780201835953, 13:978-0201835953.
  • [4] Ehrenfeucht A, Kleijn J, Kounty M, Rozenberg G. Evolving reaction systems. Theoretical Computer Science 2017;682:79-92. URL https://doi.org/10.1016/j.tcs.2016.12.031.
  • [5] Ehrenfeucht A, Kleijn J, Kounty M, Rozenberg G. Qualitative and quantitative aspects of a model for processes inspired by the functioning of the living cell. In: E. Katz (Ed.), Biomolecular Information Processing: From Logic Systems to Smart Sensors and Actuators, 1, Wiley-VCH Verlag GmbH & Co. KGaA, Potsdam, NY. 2012 pp. 207-223.
  • [6] Ehrenfeucht A, Petre I, Rozenberg G. Reaction systems: A model of computation inspired by the functioning of the living cell. In: S. Konstantinidis, N. Moreira, R. Reis, J. Shallit (Eds.), The Role of Theory in Computer Science - Essays Dedicated to Janusz Brzozowski. World Scientific, 2017, pp. 1-32. URL https://doi.org/10.1142/9789813148208_0001.
  • [7] Ehrenfeucht A, Rozenberg G. Reaction systems. Fundamenta Informaticae 2006;76:1-18.
  • [8] Ehrenfeucht A, Rozenberg G. Zoom structures and reaction systems yield exploration systems. International Journal of Foundations of Computer Science 2014;25(3):275-306. URL https://doi.org/10.1142/S0129054114500142.
  • [9] Ehrenfeucht A, Rozenberg G. Standard and ordered zoom structures. Theoretical Computer Science 2015;608(P1):4-5. doi:10.1016/j.tcs.2015.07.040.
  • [10] Frege G. Grundgesetzen der Arithmetik, 2. Verlag von Hermann Pohle, Jena, 1903. URL http://www.korpora.org/Frege/PDF/gga2ocorr.pdf,http://www.korpora.org/Frege.
  • [11] Goldin D, Smolka S, Wegner P (Eds.). Interactive Computation: The New Paradigm. Springer, Heidelberg, 2006. ISBN-354034666X.
  • [12] Heller M. The Ontology of Physical Objects. Four Dimensional Hunks of Matter. Cambridge Studies in Philosophy, Cambridge University Press, Cambridge, UK, 1990. ISBN-9780521069496, 9780521385442.
  • [13] Jankowski A. Interactive Granular Computations in Networks and Systems Engineering: A Practical Perspective. Lecture Notes in Networks and Systems, Springer, Heidelberg, 2017. doi:10.1007/978-3-319-57627-5.
  • [14] Mitchell M (Ed.). Complexity: A Guided Tour. Oxford University Press, Oxford, UK, 2009. ISBN-13:978-0199798100, 10:0199798109.
  • [15] Pawlak Z. Rough sets. International Journal of Computer and Information Sciences 1982;11:341-356.
  • [16] Pawlak Z. Rough Sets: Theoretical Aspects of Reasoning about Data, System Theory, Knowledge Engineering and Problem Solving, vol. 9. Kluwer Academic Publishers, Dordrecht, The Netherlands, 1991. doi:10.1007/978-94-011-3534-4.
  • [17] Pawlak Z, Skowron A. Rudiments of rough sets. Information Sciences 2007;177(1):3-27. doi:10.1016/j.ins.2006.06.003.
  • [18] Reisig W. Understanding Petri Nets: Modeling Techniques, Analysis Methods, Case Studies. Springer, Heidelberg, 2013. doi:10.1007/978-3-642-33278-4.
  • [19] Salomaa A. Functions and sequences generated by reaction systems. Theoretical Computer Science 2012;466:87-96. URL https://doi.org/10.1016/j.tcs.2012.07.022.
  • [20] Skowron A, Jankowski A. Interactive computations: Toward risk management in interactive intelligent systems. Natural Computing 2016;15(3):465-476. doi:10.1007/s11047-015-9486-5.
  • [21] Skowron A, Jankowski A. Rough sets and interactive granular computing. Fundamenta Informaticae 2016;147(2-3):371-385. doi:10.3233/FI-2016-1413.
  • [22] Skowron A, Nguyen HS. Rough sets: From rudiments to challenges. In: A. Skowron, Z. Suraj (Eds.), Rough Sets and Intelligent Systems. Professor Zdzislaw Pawlak in Memoriam, Springer, Heidelberg, Series Intelligent Systems Reference Library, vol. 42-43. 2013 pp. 75-173. doi:10.1007/978-3-642-30344-9_3.
  • [23] Skowron A, Stepaniuk J. Hierarchical modelling in searching for complex patterns: Constrained sums of information systems. Journal of Experimental and Theoretical Artificial Intelligence 2005;17(1-2):83-102. URL https://doi.org/10.1080/09528130512331315873.
  • [24] Suraj Z. Rough set methods for the synthesis and analysis of concurrent processes. In: L. Polkowski, T. Y. Lin, S. Tsumoto (Eds.), Rough Set Methods and Applications: New Developments in Knowledge Discovery in Information Systems, Springer-Verlag/Physica-Verlag, Heidelberg, Studies in Fuzziness and Soft Computing, vol. 56. 2000 pp. 379-488. doi:10.1007/978-3-7908-1840-6_8.
  • [25] Vapnik V. Statistical Learning Theory. John Wiley & Sons, New York, NY, 1998. ISBN-13:978-0471030034, 10:0471030031.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
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