CSP search with responsibility sets and kernels

Igor Razgon; Amnon Meisels

CSP search with responsibility sets and kernels

Igor Razgon, Amnon Meisels

Ben-Gurion University of the Negev

Research output: Contribution to journal › Conference article › peer-review

Abstract

We introduce data structures called responsibility set and kernel. We present an algorithm FC-RK, which is a modification of FC that maintains these structures and uses them for pruning of the search space. According to our experimental evaluation, FC-RK outperforms FC-CBJ on constraint networks encoding graph k-coloring instances and on non-dense random binary constraint networks.

Original language	English
Pages (from-to)	1533-1534
Number of pages	2
Journal	IJCAI International Joint Conference on Artificial Intelligence
State	Published - 2005
Externally published	Yes
Event	19th International Joint Conference on Artificial Intelligence, IJCAI 2005 - Edinburgh, United Kingdom Duration: 30 Jul 2005 → 5 Aug 2005

Cite this

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title = "CSP search with responsibility sets and kernels",

abstract = "We introduce data structures called responsibility set and kernel. We present an algorithm FC-RK, which is a modification of FC that maintains these structures and uses them for pruning of the search space. According to our experimental evaluation, FC-RK outperforms FC-CBJ on constraint networks encoding graph k-coloring instances and on non-dense random binary constraint networks.",

author = "Igor Razgon and Amnon Meisels",

year = "2005",

language = "אנגלית",

pages = "1533--1534",

journal = "IJCAI International Joint Conference on Artificial Intelligence",

issn = "1045-0823",

publisher = "International Joint Conferences on Artificial Intelligence",

note = "19th International Joint Conference on Artificial Intelligence, IJCAI 2005 ; Conference date: 30-07-2005 Through 05-08-2005",

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AU - Meisels, Amnon

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AB - We introduce data structures called responsibility set and kernel. We present an algorithm FC-RK, which is a modification of FC that maintains these structures and uses them for pruning of the search space. According to our experimental evaluation, FC-RK outperforms FC-CBJ on constraint networks encoding graph k-coloring instances and on non-dense random binary constraint networks.

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SN - 1045-0823

SP - 1533

EP - 1534

JO - IJCAI International Joint Conference on Artificial Intelligence

JF - IJCAI International Joint Conference on Artificial Intelligence

T2 - 19th International Joint Conference on Artificial Intelligence, IJCAI 2005

Y2 - 30 July 2005 through 5 August 2005

ER -

CSP search with responsibility sets and kernels

Abstract

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