Titlebook: Logic Programming; 18th International C Peter J. Stuckey Conference proceedings 2002 Springer-Verlag Berlin Heidelberg 2002 computational l

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gentle

Towards a Declarative Query and Transformation Language for XML and Semistructured Data: Simulation languages have been proposed that are inspired from functional languages (such as XSLT [.]) and/or database query languages (such as XQuery [.]). This paper addresses applying logic programming concepts and techniques to designing a declarative, rule-based query and transformation language for XML a

Incorruptible

A Proof-Theoretic Foundation for Tabled Higher-Order Logic Programming typed λ-terms and the body of clauses may contain implication and universal quantification. In this paper, we describe . where some redundant computation is eliminated by memoizing sub-computation and re-using its result later. This work extends Tamaki and Sato’s search strategy based on memoizatio

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GORGE

A Model Theoretic Semantics for Multi-level Secure Deductive Databases negation. We also define a bottom-up procedure to compute unique models of stratified MultiLog databases. Finally, we also establish the equivalence of MultiLog’s three logical characterizations — model theory, fixpoint theory and proof theory.

Ossification

A Different Look at Garbage Collection for the WAMd start for the formal specification of the garbage collection process and it shows a potential for new compile time analyses that can improve run time memory management. Choice point trimming is used as a vehicle to show selective liveness of data, so its relation to the more common stack maps is established.

Scintigraphy

Reasoning about Actions with CHRs and Finite Domain Constraintsonstraint solver is used as the kernel of a high-level programming language for agents that reason and plan. Experiments have shown that the constraint solver exhibits excellent computational behavior and scales up well.

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VEIL

Learning in Logic with RichProlog and .. queries (as a side effect of an inductive inference followed by a deductive inference). RichProlog can be used to learn: a learning problem is expressed as a usual logic program, supplemented with data, and solved by asking a .. query. The output is correct in the limit, ., when sufficient data have been provided.

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