Vidal's libraryTitle: | Backtracking in Distributed Constraint Networks |
Author: | Youssef Hamadi, Christian Bessiére, and Jo\"el Quinqueton |
Book Tittle: | Proceedings of the European Conference on Artificial Intelligence |
Pages: | 219--223 |
Year: | 1998 |
Abstract: | The adaptation of software technology to distributed environments will be an important challenge in the next few years. In the scope of constraint reasoning, few works have been published on the adaptation of algorithms searching for a solution in a constraint network to distributed constraint networks. This paper presents a new search procedure for finding a solution in a distributed constraint network. Although based on the principle of backtracking to ensure the completeness of search, this procedure allows a high level of asynchronism, i.e., simultaneous search on independent parts of the network. Furthermore, it ts its behavior to the structure of the constraint graph in order to minimize message passing and to avoid useless restorations when a dead-end is reached. We also present a generic distributed method for computing any variable ordering heuristic. |
Cited by 50 - Google Scholar
@InProceedings{hamadi98a,
author = {Youssef Hamadi and Christian Bessi\'{e}re and Jo\"el
Quinqueton},
title = {Backtracking in Distributed Constraint Networks},
booktitle = {Proceedings of the European Conference on Artificial
Intelligence},
address = {Brighton, UK},
year = 1998,
pages = {219--223},
abstract = {The adaptation of software technology to distributed
environments will be an important challenge in the
next few years. In the scope of constraint
reasoning, few works have been published on the
adaptation of algorithms searching for a solution in
a constraint network to distributed constraint
networks. This paper presents a new search procedure
for finding a solution in a distributed constraint
network. Although based on the principle of
backtracking to ensure the completeness of search,
this procedure allows a high level of asynchronism,
i.e., simultaneous search on independent parts of
the network. Furthermore, it ts its behavior to the
structure of the constraint graph in order to
minimize message passing and to avoid useless
restorations when a dead-end is reached. We also
present a generic distributed method for computing
any variable ordering heuristic.},
keywords = {multiagent dcsp},
googleid = {jVe9pMcDvgcJ:scholar.google.com/},
url = {http://jmvidal.cse.sc.edu/library/hamadi98a.pdf},
cluster = {557887559837767565}
}
Last modified: Wed Mar 9 10:14:37 EST 2011