Bharat Jayaraman, Mauricio Osorio, and K. Moon. Partial order programming (revisited). In M. Nivat V.S. Alagar, editor, Proc. AMAST, LNCS 936, pages 561--575. Springer-Verlag, 1995.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....1. specification of the constraints of the problem; 2. specification of what is to be optimized; and 3. specification of the criteria for determining the optimal solution. While several approaches to optimization have been proposed in the logic programming and deductive databases literature [20, 23, 32, 43, 48, 61, 67, 77, 84], they do not allow one to fully specify all three of the above components. Our thesis is that the concept of preference provides a natural, modular, declarative, and efficient way for expressing the three components of an optimization problem. We describe a principled extension of constraint ....

....A program in the framework was a set of assertions of the form u i w f i ( v) for i = 1; n, where each f i is continuous (and therefore monotonic) in the partial order topology. The goal of the program was to compute the values of variables that would minimize some u j . Jayaraman et al. [43] extended this notion by using the partial order to define functions. The use of non monotonic functions was allowed modulo stratification. They also introduced conditional partial order assertions of the form: f(terms) expression condition: f(terms) expression condition: Multiple ....

[Article contains additional citation context not shown here]

B. Jayaraman, M. Osorio, and K. Moon. Partial Order Programming (Revisited). In Proc. Algebraic Methods and Software Technology, 1995.

....encoded in the terms to be unified, and is equivalent to intersecting the collections of elements the terms represent. Also Jayaraman, Osorio and Moon base their partial order programming paradigm on a lattice structure, and are specially interested on the complete lattice of finite sets [Jayaraman et al. 1995]. In their paradigm they pursue the aim to integrate sets into logic programming, and to consider them as basic data structure on which the paradigm relies. But in this framework no deduction mechanisms are given to validate order related functional expressions. To summarize, in a future work it ....

Jayaraman, B., Osorio, M., and Moon, K. (1995). Partial order programming (revisited). In Proc. Algebraic Methodology and Software Technology (AMAST), pages 561--575.

....encoded in the terms to be unified, and is equivalent to intersecting the collections of elements the terms represent. Also Jayaraman, Osorio and Moon base their partial order programming paradigm on a lattice structure, and are specially interested on the complete lattice of finite sets [7]. In their paradigm they pursue the aim to integrate sets into logic programming, and to consider them as basic data structure on which the paradigm relies. But in this framework no deduction mechanisms are given to validate order related functional expressions. 5.2 Functions as sort constructing ....

B. Jayaraman, M. Osorio, and K. Moon. Partial order programming (revisited). In Proc. Algebraic Methodology and Software Technology (AMAST), pages 561--575, 1995.

....encoded in the terms to be unified, and is equivalent to intersecting the collections of elements the terms represent. Also Jayaraman, Osorio and Moon base their partial order programming paradigm on a lattice structure, and are specially interested on the complete lattice of finite sets [11]. In their paradigm they pursue the aim to integrate sets into logic programming, and to consider them as basic data structure on which the paradigm relies. But in this framework no deduction mechanisms are given to validate order related functional expressions. 4.2 Functions as sort constructing ....

B. Jayaraman, M. Osorio, and K. Moon. Partial order programming (revisited). In Proc. Algebraic Methodology and Software Technology (AMAST), pages 561--575, 1995.

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Bharat Jayaraman, Mauricio Osorio, and K. Moon. Partial order programming (revisited). In M. Nivat V.S. Alagar, editor, Proc. AMAST, LNCS 936, pages 561--575. Springer-Verlag, 1995.

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Bharat Jayaraman, Mauricio Osorio, and K. Moon. Partial order programming (revisited). In M. Nivat V.S. Alagar, editor, Proc. AMAST, LNCS 936, pages 561-575. Springer-Verlag, 1995.

....the transformation hLLC ; Bi substitutes the clause a 0 an by the fact a 0 . Note that by transitivity of we get a 0 :a 0 . Moreover ( a a) a is a theorem in propositional classical logic and by Modus Monens we can infer a. So, this rule is sound in propositional classical logic. In [JOM95] it is defined a language that allows to model aggregation in a natural way via POL programs. In [OJ97] we showed that this POL programs can be translated to normal programs such that the declarative semantics of a POL program corresponds to the WFS of the tranlated normal program. But we have ....

Bharat Jayaraman, Mauricio Osorio and K. Moon. Partial Order Programming, LNCS 936, pages 561-575. Springer-Verlag 1995.

....of the nature of aggregation, set grouping, negation as failure, and the relationship between them. To this end, our aimis to use the WFS semantics as a suitable underlying semantics for the translated programs. There are also other approaches. A language SuRE has been developed in [Jay92,JJ94,JOM95,OJ99,Moo97] with the aim of expressing set of and aggregation in a natural way. The operational semantics of SuRE do not need to resort to the translation approach mentioned above, because it is possible to devise a computational model for the large class of the so called cost monotonic partial order ....

B. Jayaraman, M. Osorio, and K. Moon. Partial order programming (revisited) . In M. Nivat V.S. Alagar, editor, Proc. AMAST, LNCS 936, pages 561-575. Springer-Verlag, 1995.

....of the nature of aggregation, set grouping, negation as failure, and the relationship between them. To this end, our aimis to use the WFS semantics as a suitable underlying semantics for the translated programs. There are also other approaches. A language SuRE has been developed in [Jay92,JJ94,JOM95,OJ99,Moo97] with the aim of expressing set of and aggregation in a natural way. The operational semantics of SuRE do not need to resort to the translation approach mentioned above, because it is possible to devise a computational model for the large class of the so called cost monotonic partial order ....

B. Jayaraman, M. Osorio, and K. Moon. Partial order programming (revisited) . In M. Nivat V.S. Alagar, editor, Proc. AMAST, LNCS 936, pages 561--575. Springer-Verlag, 1995.

....invoking magic rewriting dynamically for each different instance of the relaxation goal that appears in the body of a clause. In addition, we are also interested in extending the paradigm to incorporate inductive aggregates such as sum. This may be achieved by adding sets as a built in data type [8, 9]. The interaction of inductive aggregates and relaxation may provide interesting problems for research. Finally, the queries that we allow are first order queries and the bodies of arbiter clauses too are not allowed to have preferential goals. A very natural kind of query to allow is whether ....

B. Jayaraman, M. Osorio, and K. Moon. Partial Order Programming (Revisited). In Proc. Algebraic Methods and Software Technology, 1995.

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