Game-theoretic rough sets

Game-theoretic rough sets are the use of rough sets to induce three-way classification decisions. The positive, negative, and boundary regions can be interpreted as regions of acceptance, rejection, and deferment decisions, respectively. The probabilistic rough set model extends the conventional rough sets by providing a more effective way of classifying objects. A main result of probabilistic rough sets is the interpretation of three-way decisions using a pair of probabilistic thresholds. The game-theoretic rough set model determines and interprets the required thresholds by utilizing a game-theoretic environment for analyzing strategic situations between cooperative or conflicting decision-making criteria. The essential idea is to implement a game for investigating how the probabilistic thresholds may change in order to improve the rough set-based decision-making.^[1]^[2]^[3]^[4] ^[5]

References

^ Azam, Nouman; Yao, JingTao (January 2014). "Analyzing uncertainties of probabilistic rough set regions with game-theoretic rough sets". International Journal of Approximate Reasoning. 55 (1): 142–155. doi:10.1016/j.ijar.2013.03.015. ISSN 0888-613X.
^ Zhang, Yan (May 2013). "Optimizing Gini coefficient of probabilistic rough set regions using Game-Theoretic Rough Sets". 2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE. pp. 1–4. doi:10.1109/ccece.2013.6567817. ISBN 978-1-4799-0033-6. S2CID 15326233.
^ Herbert, Joseph P.; Yao, JingTao (2011). "Game-Theoretic Rough Sets". Fundamenta Informaticae. 108 (3–4): 267–286. doi:10.3233/fi-2011-423. ISSN 0169-2968.
^ Yao, J.T.; Herbert, J.P. (2008). "A Game-Theoretic Perspective on Rough Set Analysis 2008 International Forum on Knowledge Technology (IFKT'08), Chongqing". Journal of Chongqing University of Posts and Telecommunications. 20 (3): 291–298.
^ Zhang, Yan; Yao, JingTao (December 4, 2012). Rule Measures Tradeoff Using Game-Theoretic Rough Sets. International Conference on Brain Informatics. Macau, China: Springer Berlin Heidelberg. pp. 348–359. doi:10.1007/978-3-642-35139-6_33. Retrieved 2021-12-12.

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[1] Azam, Nouman; Yao, JingTao (January 2014). "Analyzing uncertainties of probabilistic rough set regions with game-theoretic rough sets". International Journal of Approximate Reasoning. 55 (1): 142–155. doi:10.1016/j.ijar.2013.03.015. ISSN 0888-613X.

[2] Zhang, Yan (May 2013). "Optimizing Gini coefficient of probabilistic rough set regions using Game-Theoretic Rough Sets". 2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE. pp. 1–4. doi:10.1109/ccece.2013.6567817. ISBN 978-1-4799-0033-6. S2CID 15326233.

[3] Herbert, Joseph P.; Yao, JingTao (2011). "Game-Theoretic Rough Sets". Fundamenta Informaticae. 108 (3–4): 267–286. doi:10.3233/fi-2011-423. ISSN 0169-2968.

[4] Yao, J.T.; Herbert, J.P. (2008). "A Game-Theoretic Perspective on Rough Set Analysis 2008 International Forum on Knowledge Technology (IFKT'08), Chongqing". Journal of Chongqing University of Posts and Telecommunications. 20 (3): 291–298.

[5] Zhang, Yan; Yao, JingTao (December 4, 2012). Rule Measures Tradeoff Using Game-Theoretic Rough Sets. International Conference on Brain Informatics. Macau, China: Springer Berlin Heidelberg. pp. 348–359. doi:10.1007/978-3-642-35139-6_33. Retrieved 2021-12-12.

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