Application of the Method of Editing and Condensing in the Process of Global Decision-making

• Autorzy: Wakulicz-Deja A. , Przybyła-Kasperek M.
• Języki publikacji: EN

Abstrakty

EN

The paper presents the process of taking global decisions on the basis of the knowledge of local decision systems, in which sets of conditional attributes are different but not necessarily disjoint. We propose 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. An editing and a condensing algorithm have been used in the process of global decision making. Also a density-based algorithm has been used in the process of taking global decisions to resolve conflicts. Furthermore, the paper presents the results of experiments conducted using some data sets from UCI repository.

Słowa kluczowe

EN

decision systems; global decision; editing algorithm; condensing algorithm; density-based algorithm

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2011
• Tom: Vol. 106, nr 1
• Strony: 93--117
• Opis fizyczny: Bibliogr. 32 poz., tab.

Twórcy

autor

Wakulicz-Deja A.

autor

Przybyła-Kasperek M.

• Silesian University, Institute of Computer Science, ul. Będzińska 39, 41-200 Sosnowiec, Poland,

Bibliografia

• [1] Bazan, J., Peters, J., Skowron, A., Nguyen, H., Szczuka, M.: Rough set approach to pattern extraction from classifiers, In: Electronic Notes in Theoretical Computer Science 82, Elsevier Science Publishers, 2003.
• [2] Caragea, D.: Learning Classifiers from Distributed, Semantically Heterogeneous, Autonomous Data Sources, PhD thesis, Iowa State University, 2004.
• [3] Chawla, N., Eschrich, S., Hall, L.: Creating Ensembles of Classifiers, IEEE International Conference on Data Mining, 580-581, 2001.
• [4] Deja, R.: Conflict Analysis, Rough Sets; New Developments, In: Polkowski, L. (eds.) Studies in Fuzziness and Soft Computing, Physical-Verlag, 2000.
• [5] Delimata, P., Marszal-Paszek, B., Moshkov, M., Paszek, P., Skowron, A., Suraj, Z.: Comparison of Some Classification Algorithms Based on Deterministic and Nondeterministic Decision Rules, T. Rough Sets 12, 90-105, 2010.
• [6] Ester, M., Kriegel, H., Sander, J., Xu, X.: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise, In: Proceedings of 2nd International Conference on Knowledge Discovery and Data Mining, 226-231, KDD, 1996.
• [7] Hart, P.: The condensed nearest neighbor rule, IEEE Transactions on Information Theory 16, 515-516, 1968.
• [8] Jiang, W., Zhang, X., Cohen, A., Ras, Z.: Multiple Classifiers for Different Features in Timbre Estimation, Advances in Intelligent Information Systems, 335-356, 2010.
• [9] Kargupta, H., Park, B., Johnson, E., Sanseverino, E., Silvestre, L., Hershberger, D.: Collective DataMining From Distributed Vertically Partitioned Feature Space, InWorkshop on distributed data mining. International ConferenceonKnowledge Discovery and Data Mining, 1998.
• [10] Krzyśko, M., Wołyński, W., Górecki, T., Skorzybut, M.: Systemy uczące się. Rozpoznawanie wzorców, analiza skupień i redukcja wymiarowości, WNT, Warsaw, 2008.
• [11] Kuncheva, L.: Combining Pattern Classifiers Methods and Algorithms, John Wiley & Sons, 2004.
• [12] Michalski, R., Wojtusiak, J.: The Distribution Approximation Approach to Learning from Aggregated Data, Reports of the Machine Learning and Inference Laboratory, MLI 08-2, George Mason University, Fairfax, VA, 2008.
• [13] Pawlak, Z.: On Conflicts, Int. J. of Information and Computer Science 11, 344-356, 1984.
• [14] Pawlak, Z.: Rough Sets: Theoretical aspects of reasoning about data, Kluwer Academic Publishers, Boston, 1991.
• [15] Pawlak, Z.: An Inquiry Anatomy of Conflicts, Journal of Information Sciences 109, 65-78, 1998.
• [16] Polkowski, L., Skowron, A.: Towards adaptive calculus of granules, Zadeh, L.A., Kacprzyk, J. (eds.): Computing with Words in Information/Intelligent Systems 1-2, Physica-Verlag, Heidelberg, 201-227, 1999.
• [17] Polkowski, L., Skowron, A.: Rough mereological calculi of granules: A rough set approach to computation, Computational Intelligence 17(3), 472-492, 2001.
• [18] Polkowski, L., Araszkiewicz, B.: A rough set approach to estimating the game value and the Shapley value from data, Fundamenta Informaticae 53, 335-343, 2003.
• [19] Polkowski, L.: The Paradigm of Granular Rough Computing: Foundations and Applications, In: Zhang, D., Wang, Y., Kinsner,W. (eds.) Proceedings of the Six IEEE International Conference on Cognitive Informatics, ICCI 2007, Lake Tahoe, CA, USA, August 6-8, 145-153. IEEE, Los Alamitos, 2007.
• [20] Polkowski, L., Artiemjew, P.: On Granular Rough Computing with Missing Values, In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, 271--279. Springer, Heidelberg ,2007.
• [21] Skowron, A., Deja, R.: On Some Conflict Models and Conflict Resolutions, Romanian Journal of Information Science and Technology 3(1-2), 69-82, 2002.
• [22] Skowron, A., Wang, H., Wojna, A., Bazan, J.: Multimodal Classification: Case Studies, T. Rough Sets, 224-239, 2006.
• [23] Stepaniuk, J.: Rough - Granular Computing in Knowledge Discovery and Data Mining, Springer-Verlag, Berlin, 2008.
• [24] Straffin, P.: Game Theory and Strategy, Mathematical Association of America, Washington, 1993.
• [25] ´ Slezak, D., Wróblewski, J., Szczuka, M.: Neural network architecture for synthesis of the probabilistic rule based classifiers, In: Electronic Notes in Theoretical Computer Science 82, Elsevier Science Publishers, 2003.
• [26] Torra, V., Narukawa, Y.: Modeling Decisions Information Fusion and Aggregation Operators, Springer-Verlag, Berlin, 2007.
• [27] Wakulicz-Deja, A., Przybyła-Kasperek, M.: Hierarchiczny system wieloagentowy, ZN Pol. ´ Sl. Studia Informatica Vol. 28, No. 4 (74), 63-80, 2007.
• [28] Wakulicz-Deja, A., Przybyła-Kasperek, M.: Hierarchical Multi-Agent System, Recent Advances in Intelligent Information Systems, Academic Publishing House EXIT, 615-628, 2009.
• [29] Wakulicz-Deja, A., Przybyła-Kasperek, M.: Podejmowanie decyzji globalnej z zastosowaniem hierarchicznego systemu wieloagnetowego oraz algorytmu mrówkowego, ZN Pol. ´ Sl. Studia Informatica Vol. 30, No. 2A(83), 213-227, 2009.
• [30] Wakulicz-Deja, A., Przybyła-Kasperek, M.: Global decisions Taking on the Basis of Multi-Agent System with a Hierarchical Structure and Density-Based Algorithm, Concurrency Specification and Programming CS&P, Uniwersytet Warszawski, 616-627, 2009.
• [31] Wilson, D.: Asymptotic properties of nearest neighbor rules using edited data, IEEE Transactions on Systems, Man, and Cybernetics, SMC-2, 408-421, 1972.
• [32] Wojna, A.: Analogy-Based Reasoning in Classifier Construction, T. Rough Sets: 277-374, 2005.