Abstract
Multiple criteria decision analysis plays an important role in many real life problems found in business, economics, management, governmental and political disputes. The game-theoretic rough set model (GTRS) is a recent extension to rough set theory for intelligent decision making observed with game-theoretic formulation. In this article, we extend GTRS for formulating and analyzing multiple criteria decision making problems in rough sets. Basic concepts of the model are defined, reviewed and analyzed in the context of multiple criteria. Applicability of GTRS is demonstrated by considering different examples, including multiple criteria effective classification, rule mining and feature selection.
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Azam, N., Yao, J.T.: Classifying Attributes with Game-Theoretic Rough Sets. In: Watada, J., Watanabe, T., Phillips-Wren, G., Howlett, R.J., Jain, L.C. (eds.) Intelligent Decision Technologies. SIST, vol. 15, pp. 175–184. Springer, Heidelberg (2012)
Azam, N., Yao, J.T.: Game-theoretic Rough Sets for Feature Selection. In: Skowron, A., Suraj, Z. (eds.) Rough Sets and Intelligent Systems - Professor Zdzisław Pawlak in Memoriam. ISRL, vol. 43, pp. 61–78. Springer, Heidelberg (2012)
Deng, X.F., Yao, Y.Y.: An Information-Theoretic Interpretation of Thresholds in Probabilistic Rough Sets. In: Li, T., Nguyen, H.S., Wang, G., Grzymala-Busse, J., Janicki, R., Hassanien, A.E., Yu, H. (eds.) RSKT 2012. LNCS (LNAI), vol. 7414, pp. 369–378. Springer, Heidelberg (2012)
Greco, S., Matarazzo, B., Slowinski, R.: Parameterized rough set model using rough membership and bayesian confirmation measures. International Journal of Approximate Reasoning 49(2), 285–300 (2008)
Herbert, J.P., Yao, J.T.: Analysis of Data-Driven Parameters in Game-Theoretic Rough Sets. In: Yao, J., Ramanna, S., Wang, G., Suraj, Z. (eds.) RSKT 2011. LNCS, vol. 6954, pp. 447–456. Springer, Heidelberg (2011)
Herbert, J.P., Yao, J.T.: Game-theoretic rough sets. Fundamenta Informaticae 108(3-4), 267–286 (2011)
Jia, X.Y., Li, W.W., Shang, L., Chen, J.J.: An Optimization Viewpoint of Decision-Theoretic Rough Set Model. In: Yao, J., Ramanna, S., Wang, G., Suraj, Z. (eds.) RSKT 2011. LNCS, vol. 6954, pp. 457–465. Springer, Heidelberg (2011)
Neumann, J.V., Morgenstern, O.: Theory of Games and Economic Behavior. Princeton University Press (1944)
Slezak, D., Ziarko, W.: The investigation of the bayesian rough set model. International Journal of Approximate Reasoning 40(1-2), 81–91 (2005)
Yao, J.T., Yao, Y.Y., Ziarko, W.: Probabilistic rough sets: Approximations, decision-makings, and applications. International Journal of Approximate Reasoning 49(2), 253–254 (2008)
Yao, Y.Y.: Probabilistic approaches to rough sets. Expert Systems 20(5), 287–297 (2003)
Yao, Y.Y.: Decision-Theoretic Rough Set Models. In: Yao, J., Lingras, P., Wu, W.-Z., Szczuka, M.S., Cercone, N.J., Ślęzak, D. (eds.) RSKT 2007. LNCS (LNAI), vol. 4481, pp. 1–12. Springer, Heidelberg (2007)
Yao, Y.Y.: Probabilistic rough set approximations. International Journal of Approximate Reasoning 49(2), 255–271 (2008)
Yao, Y.Y.: The superiority of three-way decisions in probabilistic rough set models. Information Sciences 181(6), 1080–1096 (2011)
Yao, Y.Y.: An Outline of a Theory of Three-Way Decisions. In: Yao, J.T., Yang, Y., Slowinski, R., Greco, S., Li, H., Mitra, S., Polkowski, L. (eds.) RSCTC 2012. LNCS (LNAI), vol. 7413, pp. 1–17. Springer, Heidelberg (2012)
Yao, Y.Y., Zhao, Y.: Attribute reduction in decision-theoretic rough set models. Information Sciences 178(17), 3356–3373 (2008)
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Azam, N., Yao, J. (2012). Multiple Criteria Decision Analysis with Game-Theoretic Rough Sets. In: Li, T., et al. Rough Sets and Knowledge Technology. RSKT 2012. Lecture Notes in Computer Science(), vol 7414. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31900-6_49
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DOI: https://doi.org/10.1007/978-3-642-31900-6_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31899-3
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