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检索条件"任意字段=26th International Conference on Principles and Practice of Constraint Programming, CP 2020"

共 51 条记录，以下是21-30 订阅

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Omissions in constraint Acquisition 26th

Omissions in Constraint Acquisition

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26th international conference on principles and practice of constraint programming, cp 2020

作者： Tsouros, Dimosthenis C. Stergiou, Kostas Bessiere, Christian Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece CNRS University of Montpellier Montpellier France

ISBN: (纸本)9783030584740

Interactive constraint acquisition is a special case of query-directed learning, also known as "exact" learning. It is used to assist non-expert users in modeling a constraint problem automatically by posting examples to the user that have to be classified as solutions or non-solutions. One significant issue that has not been addressed in the literature of constraint acquisition is the possible presence of uncertainty in the answers of the users. We address this by introducing Limited Membership Queries, where the user has the option of replying "I don’t know", corresponding to "omissions" in exact learning. We present two algorithms for handling omissions. the first one deals with omissions that are independent events, while the second assumes that omissions are related to gaps in the user’s knowledge. We present theoretical results about both methods and we evaluate them on benchmark problems. Importantly, our second algorithm can not only learn (a part of) the target network, but also the constraints that cause the user’s uncertainty. © 2020, Springer Nature Switzerland AG.

关键词： Mergers and acquisitions

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Distributed constraint-based local search

Distributed constraint-based local search

引用

12th international conference on principles and practice of constraint programming (cp 2006)

作者： Michel, Laurent See, Andrew Van Hentenryck, Pascal Univ Connecticut Storrs CT 06269 USA Brown Univ Providence RI 02912 USA

ISBN: (纸本)3540462678

Distributed computing is increasingly important at a time when the doubling of the number of transistors on a processor every 18 months no longer translates in a doubling of speed but instead a doubling of the number of cores. Unfortunately, it also places significant conceptual and implementation burden on programmers. this paper aims at addressing this challenge for constraint-based local search (CBLS), whose search procedures typically exhibit inherent parallelism stemming from multistart, restart, or population-based techniques whose benefits have been demonstrated both experimentally and theoretically. the,paper presents abstractions that allows distributed CBLS programs to be close to their sequential and parallel counterparts, keeping the conceptual and implementation overhead of distributed computing minimal. A preliminary implementation in COMET exhibits significant speed-ups in constraint satisfaction and optimization applications. the implementation also scales well with the number of machines. Of particular interest is the observation that generic abstractions of CBLS and cp, such as models and solutions, and advanced control structures such as events and closures, play a fundamental role to keep the distance between sequential and distributed CBLS programs small. As a result, the abstractions directly apply to cp programs using multistarts or restarts procedures.

关键词： constraint theory

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A Circuit constraint for Multiple Tours Problems 1

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24th international conference on the principles and practice of constraint programming (cp)

作者： Vismara, Philippe Briot, Nicolas Univ Montpellier CNRS LIRMM Montpellier France Univ Montpellier INRA Montpellier SupAgro MISTEA Montpellier France

ISBN: (数字)9783319983349

ISBN: (纸本)9783319983349;9783319983332

Routing problems appear in many practical applications. In the context of constraint programming, circuit constraints have been successfully developed to handle problems like the well-known Traveling Salesman Problem or the Vehicle Routing Problem. these kind of constraints are linked to the search for a Hamiltonian circuit in a graph. In this paper we consider a more general multiple tour problem that consists in covering a part of the graph with a set of minimal cost circuits. We define a new global constraint WEIGHTEDSUBCIRCUITS that generalizes the WeightedCircuit constraint by releasing the need to obtain a Hamiltonian circuit. It enforces multiple disjoint circuits of bounded total cost to partially cover a weighted graph, the subsets of vertices to be covered being induced by external constraints. We show that enforcing Bounds Consistency for WeightedSubCircuits is NP-hard. We propose an incomplete but polynomial filtering method based on the search for a lower bound of a weighted Steiner circuit.

关键词： Timing circuits

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Breaking Symmetries with RootClique and LexTopSort 26th

Breaking Symmetries with RootClique and LexTopSort

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26th international conference on principles and practice of constraint programming, cp 2020

作者： Fichte, Johannes K. Hecher, Markus Szeider, Stefan School of Engineering Sciences TU Dresden Dresden Germany Database and Artificial Intelligence Group TU Wien Vienna Austria Algorithms and Complexity Group TU Wien Vienna Austria

ISBN: (纸本)9783030584740

Bounded fractional hypertree width is the most general known structural property that guarantees polynomial-time solvability of the constraint satisfaction problem. Fichte et al. (cp 2018) presented a robust and scalable method for finding optimal fractional hypertree decompositions, based on an encoding to SAT Modulo theory (SMT). In this paper, we provide an in-depth study of two powerful symmetry breaking predicates that allow us to further speed up the SMT-based decomposition: RootClique fixes the root of the decomposition tree;LexTopSort fixes the elimination ordering with respect to an underlying DAG. We perform an extensive empirical evaluation of both symmetry-breaking predicates with respect to the primal graph (which is known in advance) and the induced graph (which is generated during the search). © 2020, Springer Nature Switzerland AG.

关键词： constraint satisfaction problems

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Watched Propagation of$$0$$ -$$1$$ Integer Linear constraints 26th

Watched Propagation of$$0$$ -$$1$$ Integer Linear Constraint...

引用

26th international conference on principles and practice of constraint programming, cp 2020

作者： Devriendt, Jo Lund University Lund Sweden University of Copenhagen Copenhagen Denmark

ISBN: (纸本)9783030584740

Efficient unit propagation for clausal constraints is a core building block of conflict-driven clause learning (CDCL) Boolean satisfiability (SAT) and lazy clause generation constraint programming (cp) solvers. Conflict-driven pseudo-Boolean (PB) solvers extend the CDCL paradigm from clausal constraints to integer linear constraints, also known as (linear) PB constraints. For PB solvers, many different propagation techniques have been proposed, including a counter technique which watches all literals of a PB constraint. While CDCL solvers have moved away from counter propagation and have converged on a two watched literals scheme, PB solvers often simultaneously implement different propagation algorithms, including the counter one. the question whether watched propagation for PB constraints is more efficient than counter propagation, is still open. Watched propagation is inherently more complex for PB constraints than for clauses, and several sensible variations on the idea exist. We propose a new variant of watched propagation for PB constraints and provide extensive experimental results to verify its effectiveness. these results indicate that our watched propagation algorithm is superior to counter propagation, but when paired with specialized propagation algorithms for clauses and cardinality constraints, the difference is fairly small. © 2020, Springer Nature Switzerland AG.

关键词： constraint theory

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theoretical and Experimental Results for Planning with Learned Binarized Neural Network Transition Models 26th

Theoretical and Experimental Results for Planning with Learn...

引用

26th international conference on principles and practice of constraint programming, cp 2020

作者： Say, Buser Devriendt, Jo Nordström, Jakob Stuckey, Peter J. Monash University Melbourne Australia Lund University Lund Sweden University of Copenhagen Copenhagen Denmark

ISBN: (纸本)9783030584740

We study planning problems where the transition function is described by a learned binarized neural network (BNN). theoretically, we show that feasible planning with a learned BNN model is NP-complete, and present two new constraint programming models of this task as a mathematical optimization problem. Experimentally, we run solvers for constraint programming, weighted partial maximum satisfiability, 0–1 integer programming, and pseudo-Boolean optimization, and observe that the pseudo-Boolean solver outperforms previous approaches by one to two orders of magnitude. We also investigate symmetry handling for planning problems with learned BNNs over long horizons. While the results here are less clear-cut, we see that exploiting symmetries can sometimes reduce the running time of the pseudo-Boolean solver by up to three orders of magnitude. © 2020, Springer Nature Switzerland AG.

关键词： constraint programming

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HADDOCK: A Language and Architecture for Decision Diagram Compilation 26th

HADDOCK: A Language and Architecture for Decision Diagram C...

引用

26th international conference on principles and practice of constraint programming, cp 2020

作者： Gentzel, Rebecca Michel, Laurent van Hoeve, W.-J. University of Connecticut StorrsCT06269 United States Carnegie Mellon University PittsburghPA15213 United States

ISBN: (纸本)9783030584740

Multi-valued decision diagrams (MDDs) were introduced into constraint programming over a decade ago as a powerful alternative to domain propagation. While effective MDD-propagation algorithms have been proposed for various constraints, to date no system exists that can generically compile and combine MDD propagation for arbitrary constraints. To fill this need, we introduce Haddock, a declarative language and architecture for MDD compilation. Haddock supports the specification, implementation, and composition of a broad range of MDD propagators that delivers the strength one expects from MDDs at a fraction of the development effort and with comparable performance. this paper describes the language, the framework architecture, outlines its performance credentials and demonstrates how to specify and implement novel MDD propagators. © 2020, Springer Nature Switzerland AG.

关键词： constraint theory

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Solving Satisfaction Problems Using Large-Neighbourhood Search 26th

Solving Satisfaction Problems Using Large-Neighbourhood Sear...

引用

26th international conference on principles and practice of constraint programming, cp 2020

作者： Björdal, Gustav Flener, Pierre Pearson, Justin Stuckey, Peter J. Tack, Guido Department of Information Technology Uppsala University Uppsala Sweden Faculty of Information Technology Monash University Melbourne Australia

ISBN: (纸本)9783030584740

Large-neighbourhood search (LNS) improves an initial solution, hence it is not directly applicable to satisfaction problems. In order to use LNS in a constraint programming (cp) framework to solve satisfaction problems, we usually soften some hard-to-satisfy constraints by replacing them with penalty-function constraints. LNS is then used to reduce their penalty to zero, thus satisfying the original problem. However, this can give poor performance as the penalties rarely cause propagation and therefore do not drive each cp search, and by extension the LNS search, towards satisfying the replaced constraints until very late. Our key observation is that entirely replacing a constraint is often overkill, as the propagator for the replaced constraint could have performed some propagation without causing backtracking. We propose the notion of a non-failing propagator, which is subsumed just before causing a backtrack. We show that, by only making a few changes to an existing cp solver, any propagator can be made non-failing without modifying its code. Experimental evaluation shows that non-failing propagators, when used in conjunction with penalties, can greatly improve LNS performance compared to just having penalties. this allows us to leverage the power of the many sophisticated propagators that already exist in cp solvers, in order to use LNS for solving hard satisfaction problems and for finding initial solutions to hard-to-satisfy optimisation problems. © 2020, Springer Nature Switzerland AG.

关键词： constraint satisfaction problems

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Using constraint programming to Generate Benzenoid Structures in theoretical Chemistry 26th

Using Constraint Programming to Generate Benzenoid Structure...

引用

26th international conference on principles and practice of constraint programming, cp 2020

作者： Carissan, Yannick Hagebaum-Reignier, Denis Prcovic, Nicolas Terrioux, Cyril Varet, Adrien Aix Marseille Univ CNRS Centrale Marseille ISM2 Marseille France Aix Marseille Univ Université de Toulon CNRS LIS Marseille France

ISBN: (纸本)9783030584740

Benzenoids are a subfamily of hydrocarbons (molecules that are only made of hydrogen and carbon atoms) whose carbon atoms form hexagons. these molecules are widely studied in theoretical chemistry and have a lot of concrete applications. therefore, generating benzenoids which have certain structural properties (e.g. having a given number of hexagons or having a particular structure from a graph viewpoint) is an interesting and important problem. It constitutes a preliminary step for studying their chemical properties. In this paper, we show that modeling this problem in Choco Solver and just letting its search engine generate the solutions is a fast enough and very flexible approach. It can allow to generate many different kinds of benzenoids with predefined structural properties by posting new constraints, saving the efforts of developing bespoke algorithmic methods for each kind of benzenoids. © 2020, Springer Nature Switzerland AG.

关键词： Structural properties

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Quantum-Accelerated Global constraint Filtering 26th

Quantum-Accelerated Global Constraint Filtering

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26th international conference on principles and practice of constraint programming, cp 2020

作者： Booth, Kyle E. C. O’Gorman, Bryan Marshall, Jeffrey Hadfield, Stuart Rieffel, Eleanor NASA Ames Research Center Moffett Field CA94035 United States Mountain ViewCA94043 United States University of California BerkeleyCA94720 United States

ISBN: (纸本)9783030584740

Motivated by recent advances in quantum algorithms and gate-model quantum computation, we introduce quantum-accelerated filtering algorithms for global constraints in constraint programming. We adapt recent work in quantum algorithms for graph problems and identify quantum subroutines that accelerate the main domain consistency algorithms for the alldifferent constraint and the global cardinality constraint (gcc). the subroutines are based on quantum algorithms for finding maximum matchings and strongly connected components in graphs, and provide speedups over the best classical algorithms. We detail both complete and bounded-probability frameworks for quantum-accelerated global constraint filtering algorithms within backtracking search. © 2020, Springer Nature Switzerland AG.

关键词： Quantum computers

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