Toward interactive rough-granular computing

• Autorzy: Skowron A. , Wasilewski P.
• Języki publikacji: EN

Abstrakty

EN

Computations in Rough-Granular Computing (RGC) are performed on (information) granules. The rough set approach is used in RGC for inducing granules approximating other granules about which imperfect knowledge is given only. For modeling of complex systems, it is important to extend the RGC approach to Interactive Rough-Granular Computing (IRGC) based on interactions of granules. In this paper, we discuss some fundamental issues for interaction of granules such as general scheme of interactions and the role of dynamic attributes and dynamic information systems in modeling interactive computations.

Słowa kluczowe

EN

rough sets; granular computing; interactive computations; perception based computing; perception attributes; sensory attributes; action attributes; vague concepts; approximation of complex vague concepts; ontology approximation

• Wydawca: Systems Research Institute, Polish Academy of Sciences
• Czasopismo: Control and Cybernetics
• Rocznik: 2011
• Tom: Vol. 40, no 2
• Strony: 213--235
• Opis fizyczny: Bibliogr. 57 poz., il.

Twórcy

autor

Skowron A.

autor

Wasilewski P.

• Institute of Mathematics, The University of Warsaw Banacha 2, 02-097 Warsaw, Poland,

Bibliografia

• Bara, B.G. (1995) Cognitive Science. A Developmental Approach to the Simulation of the Mind. Lawrence Erlbaum Associates, Hove.
• Barwise, J. and Seligman, J. (1997) Information Flow: The Logic of Distributed Systems. Cambridge University Press, Cambridge.
• Bazan, J. (2008) Hierarchical classifiers for complex spatio-temporal concepts,Transactions on Rough Sets IX. LNCS 5390, Springer.
• Bazan, J., Kruczek, P., Bazan-Socha, S., Skowron, A. and Pietrzyk, J.J. (2006a) Automatic planning of treatment of infants with respiratory failure through rough set modeling. In: S. Greco, Y. Hato, S. Hirano, M. Inuiguchi, S. Miyamoto, H.S. Nguyen and R. Słowiński, eds., Proceedings of the 5th International Conference on Rough Sets and Current Trends in Computing (RSCTC 2006), Kobe, Japan. LNAI 4259, Springer, Heidelberg, 418-427.
• Bazan, J., Kruczek, P., Bazan-Socha, S., Skowron, A. and Pietrzyk, J.J. (2006b) Risk pattern identification in the treatment of infants with respiratory failure through rough set modeling. In: Proc. of IPMU’2006, Paris, France, Éditions E.D.K., Paris, 2650-2657.
• Bazan, J., Peters, J.F. and Skowron, A. (2005) Behavioral pattern identification through rough set modelling. In: D. Ślęzak, J.T. Yao, J.F. Peters, W. Ziarko, and X. Hu, eds., Proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC’2005), Regina, Canada, Part II. LNAI 3642, Springer, Heidelberg, 688-697.
• Bazan, J. and Skowron, A. (2005a) Classifiers based on approximate reasoning schemes. In: B. Dunin-Kęplicz, A. Jankowski, A. Skowron and M. Szczuka, eds., Monitoring, Security, and Rescue Tasks in Multi-agent Systems (MSRAS’2004), Springer, Heidelberg, 191-202.
• Bazan, J. and Skowron,A. (2005b) On-line elimination of non-relevant parts of complex objects in behavioral pattern identification. In: S.K. Pal and S. Bandoyopadhay, eds., Proceedings of the First International Conference on Pattern Recognition and Machine Intelligence (PReMI’05), LNCS 3776, Springer, Heidelberg, 720-725.
• Bazan, J., Skowron,A. and Swiniarski,R. (2006c) Rough sets and vague concept approximation: From sample approximation to adaptive learning. Transactions on Rough Sets V: Journal Subline. LNCS 3100, Springer, 39-63.
• Breiman, L. (2001) Statistical modeling: The two cultures. Statistical Science, 16(3), 199-231.
• Bridewell, W., Langley, P., Todorovski, L. and Dzeroski, S. (2008) Inductive process modeling. Machine Learning, 71, 1-32.
• Cartwright, J. (2000) Evolution and Human Behavior: Darwinian Perspective on Human Nature. MIT Press.
• Feng, J., Jost, J. and Minping, Q., eds. (2007) Network: From Biology to Theory. Springer, Heidelberg.
• Frege, G. (1903) Grundgesetzen der Arithmetik vol. 2. Verlag von Hermann Pohle, Jena.
• Gabbay, D. (1977) Fibring Logics. Oxford University Press.
• Gabbay, D. and Pirri, F. (1997) Introduction. In: D. Gabbay, F. Pirri, eds., Combining Logics. Special Issue of Studia Logica, Studia Logica, 59, 1-4.
• Gell-Mann, M. (1994) The Quark and the Jaguar - Adventures in the Simple and the Complex. Brown and Co.
• Goldin, D., Smolka, S. and Wegner, P. (2006) eds. (2006), Interactive Computation: The New Paradigm. Springer, Heidelberg.
• Hastie, T., Tibshirani, R. and Friedman, J.H. (2008) The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer, Heidelberg.
• Jankowski, J. and Skowron, A. (2009a) Rough Granular Computing in Human-Centric Information Processing. In: K.A. Cyran, S. Kozielski, J.F. Peters, U. Stańczyk and A. Wakulicz-Deja, eds., Man-machine Interactions. Springer, Heildelberg, 23-42.
• Jankowski, J. and Skowron, A. (2009b) Wisdom Technology: A Rough-Granular Approach. In: M. Marciniak and A. Mykowiecka, eds., Bolc Festschrift. LNCS 5070, Springer, Heildelberg, 3-41.
• Leśniewski, S. (1929) Grundzüge eines neuen Systems der Grundlagen der Mathematik. Fundamenta Mathematicae, 14:1-81.
• Miikkulainen, R., Bednar, J.A., Choe, Y. and Sirosh, J. (2005) Computational Maps in the Visual Cortex. Springer, Heidelberg.
• Nguyen,H.S., Bazan, J., Skowron,A. and Nguyen, S.H. (2006) Layered learning for concept synthesis. Transactions on Rough Sets I: Journal Subline. LNCS 3100, Springer, 187-208.
• Nguyen, H.S., Jankowski, A., Peters, J.F., Skowron, A., Stepaniuk, J. and Szczuka, M. (2010) Discovery of Process Models from Data and Domain Knowledge. In: J. T. Yao, ed., Novel Developments in Granular Computing: Applications for Advanced Human Reasoning and Soft Computation, pp. 16-47, IGI Global.
• Nguyen, S.H., Nguyen, T.T. and Nguyen, H.S. (2005) Rough set approach to sunspot classification. In: D. Ślęzak, J.T. Yao, J.F. Peters, W. Ziarko and X. Hu, eds., Proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC’2005), Regina, Canada, Part II. LNAI 3642, Springer, Heidelberg, 263-272.
• Noë, A. (2005) Action in Perception. MIT Press.
• Pawlak, Z. (1982) Rough sets. International Journal of Computing and Information Sciences, 18, 341-365.
• Pawlak, Z. (1991) Theoretical Aspects of Reasoning About Data. Kluwer Academic Publishers.
• Pawlak, Z. (1992) Concurrent versus sequential - the rough sets perspective. Bulletin of the EATCS, 48, 178-190.
• Pawlak, Z. and Skowron, A. (2007) Rudiments of rough sets. Information Science, 177, 3-27.
• Pedrycz,W., Skowron, A. and Kreinovich, V., eds. (2008) Handbook of Granular Computing. John Wiley and Sons, Hoboken.
• Poggio,T. and Smale, S. (2003) The mathematics of learning: Dealing with data. Notices of the AMS, 50(5), 537-544.
• Polkowski,L. and Skowron,A. (1996) Rough mereology: A new paradigm for approximate reasoning. Int. J. of Approximate Reasoning, 15(4), 333-365.
• Ramsay, J.O. and Silverman, B.W. (2002) Applied Functional Data Analysis. Springer, Heidelberg.
• Shoham, Y. and Leyton-Brown, K. (2009) Multi-agent Systems: Algorithmic, Game Theoretic and Logical Foundations. Cambridge University Press.
• Skowron, A. and Stepaniuk, J. (2008) Rough sets and granular computing: Toward rough-granular computing. In: W. Pedrycz, A. Skowron and V. Kreinovich, eds., Handbook of Granular Computing, John Wiley & Sons, 425-448.
• Skowron,A. and Stepaniuk, J. (2010) Approximation Spaces in Rough-Granular Computing. Fundamenta Informaticae, 100, 141-157.
• Skowron, A. and Stepaniuk, J. (2011) Rough Granular Computing Based on Approximation Spaces. Information Sciences, doi:10.1016/j.ins.2011.08.001.
• Skowron, A. and Suraj, Z. (1993) Rough sets and concurrency. Bulletin of the Polish Academy of Sciences, 41, 237-254.
• Skowron, A. and Suraj, Z. (1995) Discovery of concurrent data models from experimental tables: A rough set approach. In: Proceedings of First International Conference on Knowledge Discovery and Data Mining. AAAI Press, Menlo Park, 288-293.
• Skowron, A. and Szczuka, M. (2009) Toward interactive computations: A rough-granular approach. In: J. Koronacki, S. Wierzchon, Z. Ras and J. Kacprzyk, eds., Advances in Machine Learning Vol. II, Dedicated to the Memory of Professor Ryszard Michalski. Springer, Heidelberg, 23-42.
• Skowron, A. and Wasilewski, P. (2010a) Information systems in interactive computing. In: A. Wakulicz-Deja, ed., Proceedings of Decision System Support Conference, Zakopane, Institute of Informatics, Silesian University (in print).
• Skowron, A. and Wasilewski, P. (2010b) Information systems in modeling interactive computations on granules. In: M. Szczuka, M. Kryszkiewicz, S. Ramanna, R. Jensen and Q. Hu, eds., Proceedings of the 7th International Conference on Rough Sets and Current Trends in Computing (RSCTC 2010). LNAI 6086, Springer, Heildelberg, 730-739.
• Skowron, A. and Wasilewski, P. (2011) Information Systems in Modeling Interactive Computations on Granules. Theoretical Computer Science, 412 (42), 5939-5959.
• Sycara, K. (1998) Multi-agent systems. AI Magazine, 19(2), 79-93.
• Thagard, P. (2005) Mind: Introduction to Cognitive Science (2nd ed.). MIT Press.
• The Rough Set Exploration System (RSES) (no date) http://logic.mimuw.edu.pl/∼rses (as of 5 September 2011).
• The Rough Set Interactive Classification Engine (RoughICE) (no date) http://www.mimuw.edu.pl/∼bazan/roughice (as of 5 September 2011.
• The RSES lib project homepage (no date) http://rsproject.mimuw.edu.pl (as of 5 September 2011.
• The TunedIT platform homepage (no date) http://tunedit.org/.
• Vapnik, V. (1998) Statistical Learning Theory. John Wiley & Sons.
• Wittgenstein, L. (2001) Philosophical Investigations. The German text, with revised English translation. Third edition. Translated by G.E.M. Anscombe, Blackwell.
• Zadeh, L.A. (1965) Fuzzy sets. Information and Control, 8, 333-353.
• Zadeh, L.A. (1999) From computing with numbers to computing with words- From manipulation of measurements to manipulation of perceptions. IEEE Transactions on Circuits and Systems, 45, 105-119.
• Zadeh, L.A. (2001) A new direction in AI - toward a computational theory of perceptions. AI Magazine, 22(1), 73-84.
• Zadeh, L.A. (2006) Keynote lecture at the 5th International Conference on Rough Sets and Current Trends in Computing, RSCTC, Kobe, Japan, November 6-8, 2006.