Abstract
The problem of finding the set of Pareto optimal solutions for constraints and qualitative preferences together is of great interest to many real world applications. It can be viewed as a preference constrained optimization problem where the goal is to find one or more feasible solutions that are not dominated by other feasible outcomes. Our work aims to enhance the current literature of the problem by providing solving methods targeting the problem in static and dynamic environments. We target the problem with an eye on adopting and benefiting from the current constraint solving techniques.
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References
Alanazi, E., Mouhoub, M.: Arc consistency for cp-nets under constraints. In: FLAIRS Conference (2012)
Alanazi, E., Mouhoub, M.: A framework to manage conditional constraints and qualitative preferences. In: FLAIRS Conference (to appear, 2013)
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)
Boutilier, C., Brafman, R.I., Hoos, H.H., Poole, D.: Preference-based constrained optimization with cp-nets. Computational Intelligence 20, 137–157 (2001)
Darwiche, P.A.: Modeling and Reasoning with Bayesian Networks, 1st edn. Cambridge University Press, New York (2009)
Domshlak, C., Rossi, F., Venable, K.B., Walsh, T.: Reasoning about soft constraints and conditional preferences: complexity results and approximation techniques. CoRR abs/0905.3766 (2009)
Doyle, J., Thomason, R.H.: Background to qualitative decision theory. AI Magazine 20 (1999)
Goldsmith, J., Junker, U.: Preference handling for artificial intelligence. AI Magazine 29(4), 9–12 (2008)
Kumar, V.: Algorithms for constraint satisfaction problems: A survey. AI Magazine 13(1), 32–44 (1992)
Mackworth, A.K.: Consistency in networks of relations. Artificial Intelligence 8(1), 99–118 (1977)
Prestwich, S., Rossi, F., Venable, K.B., Walsh, T.: Constrained cpnets. In: Proceedings of CSCLP 2004 (2004)
Rossi, F., Venable, K.B., Walsh, T.: Preferences in constraint satisfaction and optimization. AI Magazine 29(4), 58–68 (2008)
Wilson, N.: Consistency and constrained optimisation for conditional preferences. In: ECAI, pp. 888–894 (2004)
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Alanazi, E. (2013). Preference Constrained Optimization under Change. In: Zaïane, O.R., Zilles, S. (eds) Advances in Artificial Intelligence. Canadian AI 2013. Lecture Notes in Computer Science(), vol 7884. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38457-8_33
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DOI: https://doi.org/10.1007/978-3-642-38457-8_33
Publisher Name: Springer, Berlin, Heidelberg
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