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Pareto Optimality for Conditional Preference Networks with Comfort

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Advances and Trends in Artificial Intelligence. From Theory to Practice (IEA/AIE 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11606))

Abstract

A Conditional Preference Network with Comfort (CPC-net) graphically represents both preference and comfort. Preference and comfort indicate user’s habitual behavior and genuine decisions correspondingly. Given that these two concepts might be conflicting, we find it necessary to introduce Pareto optimality when achieving outcome optimization with respect to a given acyclic CPC-net. In this regard, we propose a backtrack search algorithm, that we call Solve-CPC, to return the Pareto optimal outcomes. The formal properties of the algorithm are presented and discussed.

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References

  1. Ahmed, S., Mouhoub, M.: Constrained optimization with partial CP-nets. In: IEEE International Conference on Systems, Man, and Cybernetics, pp. 3361–3366 (2018)

    Google Scholar 

  2. Ahmed, S., Mouhoub, M.: Extending conditional preference network with user’s genuine decisions. In: Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, pp. 4216–4223 (2018)

    Google Scholar 

  3. Ahmed, S., Mouhoub, M.: Transformation between CP-net and CPC-net. In: Proceedings of International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, pp. 292–300 (2018)

    Google Scholar 

  4. Alanazi, E., Mouhoub, M.: Variable ordering and constraint propagation for constrained CP-nets. Appl. Intell. 44(2), 437–448 (2016)

    Article  Google Scholar 

  5. Boutilier, C., Brafman, R., Domshlak, C., Hoos, H., Poole, D.: Preference-based constrained optimization with CP-nets. Comput. Intell. 20, 137–157 (2004)

    Article  MathSciNet  Google Scholar 

  6. Boutilier, C., Brafman, R.I., Domshlak, C., Hoos, H.H., Poole, D.: CP-nets: a tool for representing and reasoning with conditional ceteris paribus preference statements. J. Artif. Intell. Res. (JAIR) 21, 135–191 (2004)

    Article  MathSciNet  Google Scholar 

  7. Brafman, R.I., Domshlak, C., Shimony, S.E.: On graphical modeling of preference and importance. J. Artif. Intell. Res. 25, 389–424 (2006)

    Article  MathSciNet  Google Scholar 

  8. Dechter, R.: Constraint Processing. Morgan Kaufmann, San Francisco (2003)

    MATH  Google Scholar 

  9. Fishburn, P.C., Lavalle, I.H.: MCDA: theory, practice and the future. J. Multicriteria Decis. Anal. 8(1), 1–2 (1999)

    Article  Google Scholar 

  10. Katona, G.: Psychological Analysis of Economic Behavior. McGraw-Hill, New York (1951)

    Google Scholar 

  11. Keeney, R.L., Raiffa, H.: Decisions with Multiple Objectives: Preferences and Value Trade-Offs. Cambridge University Press, New York (1993)

    Book  Google Scholar 

  12. Triantaphyllou, E.: Multi-criteria decision making methods. In: Triantaphyllou, E. (ed.) Multi-Criteria Decision Making Methods: A Comparative Study, pp. 5–21. Springer, Boston (2000). https://doi.org/10.1007/978-1-4757-3157-6_2

    Chapter  MATH  Google Scholar 

  13. Zajonc, R.B.: Feeling and thinking: preferences need no inferences. Am. Psychol. 35(2), 151–175 (1980)

    Article  Google Scholar 

Download references

Acknowledgment

This research was funded by Natural Sciences and Engineering Research Council of Canada (RGPIN-2016-05673).

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Correspondence to Malek Mouhoub .

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Ahmed, S., Mouhoub, M. (2019). Pareto Optimality for Conditional Preference Networks with Comfort. In: Wotawa, F., Friedrich, G., Pill, I., Koitz-Hristov, R., Ali, M. (eds) Advances and Trends in Artificial Intelligence. From Theory to Practice. IEA/AIE 2019. Lecture Notes in Computer Science(), vol 11606. Springer, Cham. https://doi.org/10.1007/978-3-030-22999-3_72

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  • DOI: https://doi.org/10.1007/978-3-030-22999-3_72

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22998-6

  • Online ISBN: 978-3-030-22999-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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