Dynamic ordering for asynchronous backtracking on disCSPs

Roie Zivan; Amnon Meisels

doi:10.1007/s10601-006-8062-0

Dynamic ordering for asynchronous backtracking on disCSPs

Roie Zivan, Amnon Meisels

Department of Computer Science

Research output: Contribution to journal › Article › peer-review

29 Scopus citations

Abstract

An algorithm that performs asynchronous backtracking on distributed CSPs, with dynamic ordering of agents is proposed, ABT\_DO. Agents propose reorderings of lower priority agents and send these proposals whenever they send assignment messages. Changes of ordering triggers a different computation of Nogoods. The dynamic ordered asynchronous backtracking algorithm uses polynomial space, similarly to standard ABT. The ABT\_DO algorithm with three different ordering heuristics is compared to standard ABT on randomly generated DisCSPs. A Nogood-triggered heuristic, inspired by dynamic backtracking, is found to outperform static order ABT by a large factor in run-time and improve the network load.

Original language	English
Pages (from-to)	179-197
Number of pages	19
Journal	Constraints
Volume	11
Issue number	2-3
DOIs	https://doi.org/10.1007/s10601-006-8062-0
State	Published - 1 Jul 2006

Keywords

Distributed AI
Distributed Constraint satisfaction
Search

ASJC Scopus subject areas

Software
Discrete Mathematics and Combinatorics
Computational Theory and Mathematics
Artificial Intelligence

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10.1007/s10601-006-8062-0

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title = "Dynamic ordering for asynchronous backtracking on disCSPs",

abstract = "An algorithm that performs asynchronous backtracking on distributed CSPs, with dynamic ordering of agents is proposed, ABT\_DO. Agents propose reorderings of lower priority agents and send these proposals whenever they send assignment messages. Changes of ordering triggers a different computation of Nogoods. The dynamic ordered asynchronous backtracking algorithm uses polynomial space, similarly to standard ABT. The ABT\_DO algorithm with three different ordering heuristics is compared to standard ABT on randomly generated DisCSPs. A Nogood-triggered heuristic, inspired by dynamic backtracking, is found to outperform static order ABT by a large factor in run-time and improve the network load.",

keywords = "Distributed AI, Distributed Constraint satisfaction, Search",

author = "Roie Zivan and Amnon Meisels",

note = "Funding Information: Acknowledgments Supported by the Lynn and William Frankel Center for Computer Sciences and the Paul Ivanier Center for Robotics and Production Management.",

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AU - Meisels, Amnon

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AB - An algorithm that performs asynchronous backtracking on distributed CSPs, with dynamic ordering of agents is proposed, ABT\_DO. Agents propose reorderings of lower priority agents and send these proposals whenever they send assignment messages. Changes of ordering triggers a different computation of Nogoods. The dynamic ordered asynchronous backtracking algorithm uses polynomial space, similarly to standard ABT. The ABT\_DO algorithm with three different ordering heuristics is compared to standard ABT on randomly generated DisCSPs. A Nogood-triggered heuristic, inspired by dynamic backtracking, is found to outperform static order ABT by a large factor in run-time and improve the network load.

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Dynamic ordering for asynchronous backtracking on disCSPs

Abstract

Keywords

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