Satoh K., Aiba A., Computing Soft Constraints by Hierarchical Constraint Logic Programming, in: Journal of Information Processing, 7, 1993.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....Charles University, Faculty of Mathematics and Physics, Malostransk nmest 2 25, Praha, Czech Republic. bartak kti.mff.cuni.cz. Supported by GACR grant 201 99 D057. Constraint Logic Programming) programs [6] and it is also employed in the DeltaStar algorithm [16] and in the HCLP language CHAL [14]. The refining method is general it can be applied to any constraint hierarchy using any comparator. However, this method requires the solution to be recomputed from scratch after every change (e.g. after adding or removing a constraint) The local propagation algorithms were designed to allow ....

Satoh K., Aiba A., Computing Soft Constraints by Hierarchical Constraint Logic Programming, in: Journal of Information Processing, 7, 1993.

....stronger constraint. Thus, for example, default behavior can be expressed in a program by weak constraints, which will be over ruled by stronger constraints when non default behavior is required. The restriction to best solutions of a constraint hierarchy can be viewed as a form of circumscription [219]. Each of the above approaches has some programming advantages over the other, in certain applications, but both have problems as general purpose methods. While the first approach works well when there is a natural choice of objective function suggested by the problem, in general there is no ....

K. Satoh & A. Aiba, Computing Soft Constraints by Hierarchical Constraint Logic Programming, Journal of Information Processing, 7, 1993, to appear.

....might be most appropriate for a given application. All of the sample programs here are for the domain of the real numbers. However, implementations of HCLP languages for other domains are of course possible as well, and would be useful for other applications. For example, the HCLP language CHAL [62, 63] includes support for the domain of the booleans, as well as for polynomial equations over algebraic numbers. See also the discussion of this language in Section 10 on related work. Regarding the comparator to be used, if it is significant, we will refer to the program as e.g. an HCLP(R;LPB) one; ....

....to specify an ordering on the interpretations that satisfy the required constraints. The theory is quite general, and can accommodate all of the comparators described in Section 2. However, since it is defined by second order formulae, it is not in general computable. In subsequent work [62, 63], Satoh and Aiba present an alternative theory that restricts the constraints to a single domain D, so that they can be expressed in a first order formula. This theory is similar to the one presented here, with the following differences: first, only the locally predicate better comparator is ....

[Article contains additional citation context not shown here]

Ken Satoh and Akira Aiba. Computing Soft Constraints by Hierarchical Constraint Logic Programming. Technical Report TR-610, Institute for New Generation Computer Technology, Tokyo, January 1991.

....can categorize the algorithms into the following three approaches: The refining method first satisfies the strongest level, and then, weaker levels successively. It is mainly employed in constraint logic programming languages such as HLCP(R, with the DeltaStar constraint solver [90] and CHAL [77]. The optimization approach transforms constraint hierarchies into optimization problems by assigning appropriate weights to strengths. It is adopted in recent constraint solvers for GUIs such as Cassowary and QOCA [12] Local propagation gradually solves hierarchies by repeatedly selecting ....

Satoh, K. and A. Aiba, "Computing Soft Constraints by Hierarchical Constraint Logic Programming," Tech. Rep. TR-610, ICOT, Japan, Jan. 1991. BIBLIOGRAPHY 113

....satisfaction algorithms proposed. We can categorize them into the following two approaches: The refining method first satisfies the strongest level, and then, weaker levels successively. It is employed in the DeltaStar algorithm [11] and a hierarchical constraint logic programming language CHAL [10]. Local propagation gradually solves hierarchies by repeatedly selecting uniquely satisfiable constraints. It is mainly used in constraint solvers for graphical user interfaces such as DeltaBlue [4] SkyBlue [9] and DETAIL [6] First, to illustrate the refining method, suppose we have a ....

Satoh, K. and A. Aiba, "Computing Soft Constraints by Hierarchical Constraint Logic Programming," Tech. Rep. TR-610, ICOT, Japan, Jan. 1991.

....for a given application. All of the sample programs in this chapter are written for the domain of the real numbers. However, implementations of HCLP languages for other domains are of course possible as well, and would be useful for other applications. For example, the HCLP language CHAL [Satoh Aiba 91a, Satoh Aiba 91b] includes support for the domain of the booleans, as well as for polynomial equations over algebraic numbers. See also the discussion of this language in Chapter 8 on related work. Regarding the comparator to be used, if it is significant, the program will be referred to as ....

....specify an ordering on the interpretations that satisfy the required constraints. The theory is quite general, and can accommodate all of the comparators described in Chapter 2 Section 2.3. However, since it is defined by second order formulae, it is not in general computable. In subsequent work [Satoh Aiba 91a, Satoh Aiba 91b] Satoh and Aiba present an alternative theory that restricts the constraints to a single domain D, so that they can be expressed in a first order formula. This theory is similar to the one presented here, with the following differences: first, only the locally predicate better ....

[Article contains additional citation context not shown here]

Ken Satoh and Akira Aiba. Computing Soft Constraints by Hierarchical Constraint Logic Programming. Technical Report TR-610, Institute for New Generation Computer Technology, Tokyo, January 1991.

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Ken Satoh and Akira Aiba. Computing soft constraints by hierarchical constraint logic programming. Technical Report 610, Institute for New Generation Computer Technology (ICOT), 1991.

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