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Distributed constraint programming with agents

Rolf, Carl Christian LU and Kuchcinski, Krzysztof LU (2011) International Conference on Adaptive and Intelligent Systems (ICAIS 2011) In Lecture notes in computer science 6943. p.320-331
Abstract
Many combinatorial optimization problems lend themselves to be modeled as distributed constraint optimization problems (DisCOP). Problems such as job shop scheduling have an intuitive matching between agents and machines. In distributed constraint problems, agents control variables and are connected via constraints. We have equipped these agents with a full constraint solver. This makes it possible to use global constraint and advanced search schemes.



By empowering the agents with their own solver, we overcome the low performance that often haunts distributed constraint satisfaction problems (DisCSP). By using global constraints, we achieve far greater pruning than traditional DisCSP models. Hence, we dramatically reduce... (More)
Many combinatorial optimization problems lend themselves to be modeled as distributed constraint optimization problems (DisCOP). Problems such as job shop scheduling have an intuitive matching between agents and machines. In distributed constraint problems, agents control variables and are connected via constraints. We have equipped these agents with a full constraint solver. This makes it possible to use global constraint and advanced search schemes.



By empowering the agents with their own solver, we overcome the low performance that often haunts distributed constraint satisfaction problems (DisCSP). By using global constraints, we achieve far greater pruning than traditional DisCSP models. Hence, we dramatically reduce communication between agents.



Our experiments show that both global constraints and advanced search schemes are necessary to optimize job shop schedules using DisCSP. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
Lecture notes in computer science
editor
Manthiri. M, Abbas and
volume
6943
pages
12 pages
publisher
Springer
conference name
International Conference on Adaptive and Intelligent Systems (ICAIS 2011)
external identifiers
  • wos:000306980700032
  • scopus:80053310054
ISSN
0302-9743
ISBN
978-3-642-23857-4
DOI
10.1007/978-3-642-23857-4_32
language
English
LU publication?
yes
id
d17e8e7b-8813-4607-9e74-1d7f35302187 (old id 2064283)
date added to LUP
2011-08-18 13:55:55
date last changed
2017-02-19 04:29:22
@inproceedings{d17e8e7b-8813-4607-9e74-1d7f35302187,
  abstract     = {Many combinatorial optimization problems lend themselves to be modeled as distributed constraint optimization problems (DisCOP). Problems such as job shop scheduling have an intuitive matching between agents and machines. In distributed constraint problems, agents control variables and are connected via constraints. We have equipped these agents with a full constraint solver. This makes it possible to use global constraint and advanced search schemes.<br/><br>
<br/><br>
By empowering the agents with their own solver, we overcome the low performance that often haunts distributed constraint satisfaction problems (DisCSP). By using global constraints, we achieve far greater pruning than traditional DisCSP models. Hence, we dramatically reduce communication between agents. <br/><br>
<br/><br>
Our experiments show that both global constraints and advanced search schemes are necessary to optimize job shop schedules using DisCSP.},
  author       = {Rolf, Carl Christian and Kuchcinski, Krzysztof},
  booktitle    = {Lecture notes in computer science},
  editor       = {Manthiri. M, Abbas},
  isbn         = {978-3-642-23857-4},
  issn         = {0302-9743},
  language     = {eng},
  pages        = {320--331},
  publisher    = {Springer},
  title        = {Distributed constraint programming with agents},
  url          = {http://dx.doi.org/10.1007/978-3-642-23857-4_32},
  volume       = {6943},
  year         = {2011},
}