Abstract
Constrained objects provide a suitable object-oriented style for modeling systems under constraints. A set of classes is defined to represent a problem, whose state is then controlled by a constraint satisfaction engine. This engine is commonly a black-box based on a predefined and non-customizable search strategy. This system rigidity, of course, does not allow users to tune models in order to improve the search process. In this paper we target this issue by presenting an extensible formalism to define a wide range of search options so as to customize, improve and/or analyze the search process of constrained object models.
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References
Gecode System, http://www.gecode.org
s-COMMA System, http://www.inf.ucv.cl/~rsoto/s-comma
Borning, A.H.: The Programming Languages Aspects of ThingLab, a Constraint-Oriented Simulation Laboratory. ACM TOPLAS 3(4), 353–387 (1981)
Diaz, D., Codognet, P.: The gnu prolog system and its implementation. In: SAC (2), pp. 728–732 (2000)
Frisch, A.M., et al.: The design of essence: A constraint language for specifying combinatorial problems. In: IJCAI, pp. 80–87 (2007)
Granvilliers, L., et al.: Algorithm 852: Realpaver: an interval solver using constraint satisfaction techniques. ACM Trans. Math. Softw. 32(1), 138–156 (2006)
Wallace, M., et al.: Eclipse: A platform for constraint logic programming (1997)
Nethercote, N., et al.: Minizinc: Towards a standard cp modelling language. In: Bessière, C. (ed.) CP 2007. LNCS, vol. 4741, Springer, Heidelberg (2007)
Rafeh, R., et al.: From zinc to design model. In: PADL, pp. 215–229 (2007)
Rossi, F.: Handbook of Constraint Programming. Elsevier, Amsterdam (2006)
Gelle, E., Faltings, B.: Solving mixed and conditional constraint satisfaction problems. Constraints 8(2), 107–141 (2003)
Jayaraman, B., Tambay, P.Y.: Constrained Objects for Modeling Complex Structures. In: OOPSLA, Minneapolis, USA (2000)
Apt, K.R.: Principles of Constraint Programming. Cambridge Press (2003)
Dechter, R.: Constraint Processing. Elsevier, Amsterdam (2003)
Van Hentenryck, P.: The OPL Language. The MIT Press, Cambridge (1999)
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Soto, R., Granvilliers, L. (2008). Tuning Constrained Objects. In: Nguyen, N.T., Borzemski, L., Grzech, A., Ali, M. (eds) New Frontiers in Applied Artificial Intelligence. IEA/AIE 2008. Lecture Notes in Computer Science(), vol 5027. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69052-8_43
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DOI: https://doi.org/10.1007/978-3-540-69052-8_43
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