Sets and constraint logic programming

Dovier, Agostino; Piazza, Carla; Pontelli, Enrico; Rossi, Gianfranco

doi:10.1145/365151.365169

Cited by 89 publications

(125 citation statements)

References 33 publications

(50 reference statements)

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“…Many complex relations can be expressed with set constraints such as set inclusion, union, intersection, disjointness, cardinality. An example of a logic-based language for set constraints is CLP(SET ) [55]. It provides very flexible and general forms of sets, but its effectiveness is hindered by its solving approach, which is strongly non-deterministic.…”

Section: Other Variablesmentioning

confidence: 99%

Portfolio approaches in constraint programming

Amadini

2015

Constraints

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Recent research has shown that the performance of a single, arbitrarily efficient algorithm can be significantly outperformed by using a portfolio of -possibly onaverage slower-algorithms. Within the Constraint Programming (CP) context, a portfolio solver can be seen as a particular constraint solver that exploits the synergy between the constituent solvers of its portfolio for predicting which is (or which are) the best solver(s) to run for solving a new, unseen instance.In this thesis we examine the benefits of portfolio solvers in CP. Despite portfolio approaches have been extensively studied for Boolean Satisfiability (SAT) problems, in the more general CP field these techniques have been only marginally studied and used. We conducted this work through the investigation, the analysis and the construction of several portfolio approaches for solving both satisfaction and optimization problems. We focused in particular on sequential approaches, i.e., single-threaded portfolio solvers always running on the same core.We started from a first empirical evaluation on portfolio approaches for solving Constraint Satisfaction Problems (CSPs), and then we improved on it by introducing new data, solvers, features, algorithms, and tools. Afterwards, we addressed the more general Constraint Optimization Problems (COPs) by implementing and testing a number of models for dealing with COP portfolio solvers. Finally, we have come full circle by developing sunny-cp: a sequential CP portfolio solver that turned out to be competitive also in the MiniZinc Challenge, the reference competition for CP solvers.iii iv

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Section: Other Variablesmentioning

confidence: 99%

Portfolio approaches in constraint programming

Amadini

2015

Constraints

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“…The solver is formulated in a rule-based way. The number of rules is not small (as it is usual for such kind of solvers, cf., e.g., [9,7]). To make their comprehension easier, we group them so that similar ones are collected together in subsections.…”

Section: Semanticsmentioning

confidence: 99%

Constraint Logic Programming for Hedges: A Semantic Reconstruction

Dundua

Florido

Kutsia

et al. 2014

Functional and Logic Programming

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Abstract. We describe the semantics of CLP(H): constraint logic programming over hedges. Hedges are finite sequences of unranked terms, built over variadic function symbols and three kinds of variables: for terms, for hedges, and for function symbols. Constraints involve equations between unranked terms and atoms for regular hedge language membership. We give algebraic semantics of CLP(H) programs, define a sound, terminating, and incomplete constraint solver, and describe some fragments of constraints for which the solver returns a complete set of solutions.

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“…3, communication is based on operations on sets. For this reason, we decided to perform our experiments on CLP (SET ) [8], a constraint language based on sets. CLP (SET ) is an instance of the general CLP framework [14] which provides finite sets, along with a few set-based operations, as primitive objects of the language.…”

Section: Abduction and Set Operations: Experiments With Clp (Set )mentioning

confidence: 99%

An Abductive Framework for Information Exchange in Multi-agent Systems

Gavanelli

Lamma

Mello

et al. 2004

Lecture Notes in Computer Science

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Abstract. In this paper, we propose a framework for information exchange among abductive agents whose local knowledge bases are enlarged with a set of abduced hypotheses. We integrate the aspects of information exchange and abductive reasoning, and show theoretically the information inferred by the single abductive agent as a product of joint reasoning activity. We show examples, like dining philosophers, resource exchange and speculative computation, and give an implementation of the space of interactions based on CLP (SET ).

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Sets and constraint logic programming

Cited by 89 publications

References 33 publications

Portfolio approaches in constraint programming

Portfolio approaches in constraint programming

Constraint Logic Programming for Hedges: A Semantic Reconstruction

An Abductive Framework for Information Exchange in Multi-agent Systems

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