IDB-ADOPT: A depth-first search DCOP algorithm

William Yeoh; Ariel Felner; Sven Koenig

doi:10.1007/978-3-642-03251-6_9

IDB-ADOPT: A depth-first search DCOP algorithm

William Yeoh, Ariel Felner, Sven Koenig

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Many agent coordination problems can be modeled as distributed constraint optimization (DCOP) problems. ADOPT is an asynchronous and distributed search algorithm that is able to solve DCOP problems optimally. In this paper, we introduce Iterative Decreasing Bound ADOPT (IDB-ADOPT), a modification of ADOPT that changes the search strategy of ADOPT from performing one best-first search to performing a series of depth-first searches. Each depth-first search is provided with a bound, initially a large integer, and returns the first solution whose cost is smaller than or equal to the bound. The bound is then reduced to the cost of this solution minus one and the process repeats. If there is no solution whose cost is smaller than or equal to the bound, it returns a cost-minimal solution. Thus, IDB-ADOPT is an anytime algorithm that solves DCOP problems with integer costs optimally. Our experimental results for graph coloring problems show that IDB-ADOPT runs faster (that is, needs fewer cycles) than ADOPT on large DCOP problems, with savings of up to one order of magnitude.

Original language	English
Title of host publication	Recent Advances in Constraints - 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008, Revised Selected Papers
Pages	132-146
Number of pages	15
DOIs	https://doi.org/10.1007/978-3-642-03251-6_9
State	Published - 2009
Externally published	Yes
Event	13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008 - Rome, Italy Duration: 18 Jun 2008 → 20 Jun 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5655 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008
Country/Territory	Italy
City	Rome
Period	18/06/08 → 20/06/08

Bibliographical note

Funding Information:
This research was done while Ariel Felner spent his sabbatical at the University of Southern California, visiting Sven Koenig. This research has been partly supported by an NSF award to Sven Koenig under contract IIS-0350584. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied of the sponsoring organizations, agencies, companies or the U.S. government.

Keywords

ADOPT
DCOP
Distributed Constraint Optimization
Distributed Search Algorithms

Access to Document

10.1007/978-3-642-03251-6_9

Cite this

Yeoh, W., Felner, A., & Koenig, S. (2009). IDB-ADOPT: A depth-first search DCOP algorithm. In Recent Advances in Constraints - 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008, Revised Selected Papers (pp. 132-146). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5655 LNAI). https://doi.org/10.1007/978-3-642-03251-6_9

Yeoh, William ; Felner, Ariel ; Koenig, Sven. / IDB-ADOPT : A depth-first search DCOP algorithm. Recent Advances in Constraints - 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008, Revised Selected Papers. 2009. pp. 132-146 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{c2e7e6eb9b3848dfaae379d37f1704ab,

title = "IDB-ADOPT: A depth-first search DCOP algorithm",

abstract = "Many agent coordination problems can be modeled as distributed constraint optimization (DCOP) problems. ADOPT is an asynchronous and distributed search algorithm that is able to solve DCOP problems optimally. In this paper, we introduce Iterative Decreasing Bound ADOPT (IDB-ADOPT), a modification of ADOPT that changes the search strategy of ADOPT from performing one best-first search to performing a series of depth-first searches. Each depth-first search is provided with a bound, initially a large integer, and returns the first solution whose cost is smaller than or equal to the bound. The bound is then reduced to the cost of this solution minus one and the process repeats. If there is no solution whose cost is smaller than or equal to the bound, it returns a cost-minimal solution. Thus, IDB-ADOPT is an anytime algorithm that solves DCOP problems with integer costs optimally. Our experimental results for graph coloring problems show that IDB-ADOPT runs faster (that is, needs fewer cycles) than ADOPT on large DCOP problems, with savings of up to one order of magnitude.",

keywords = "ADOPT, DCOP, Distributed Constraint Optimization, Distributed Search Algorithms",

author = "William Yeoh and Ariel Felner and Sven Koenig",

note = "Funding Information: This research was done while Ariel Felner spent his sabbatical at the University of Southern California, visiting Sven Koenig. This research has been partly supported by an NSF award to Sven Koenig under contract IIS-0350584. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied of the sponsoring organizations, agencies, companies or the U.S. government.; 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008 ; Conference date: 18-06-2008 Through 20-06-2008",

year = "2009",

doi = "10.1007/978-3-642-03251-6_9",

language = "אנגלית",

isbn = "3642032508",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "132--146",

booktitle = "Recent Advances in Constraints - 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008, Revised Selected Papers",

}

Yeoh, W, Felner, A & Koenig, S 2009, IDB-ADOPT: A depth-first search DCOP algorithm. in Recent Advances in Constraints - 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5655 LNAI, pp. 132-146, 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008, Rome, Italy, 18/06/08. https://doi.org/10.1007/978-3-642-03251-6_9

IDB-ADOPT: A depth-first search DCOP algorithm. / Yeoh, William; Felner, Ariel; Koenig, Sven.
Recent Advances in Constraints - 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008, Revised Selected Papers. 2009. p. 132-146 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5655 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - IDB-ADOPT

T2 - 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008

AU - Yeoh, William

AU - Felner, Ariel

AU - Koenig, Sven

N1 - Funding Information: This research was done while Ariel Felner spent his sabbatical at the University of Southern California, visiting Sven Koenig. This research has been partly supported by an NSF award to Sven Koenig under contract IIS-0350584. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied of the sponsoring organizations, agencies, companies or the U.S. government.

PY - 2009

Y1 - 2009

N2 - Many agent coordination problems can be modeled as distributed constraint optimization (DCOP) problems. ADOPT is an asynchronous and distributed search algorithm that is able to solve DCOP problems optimally. In this paper, we introduce Iterative Decreasing Bound ADOPT (IDB-ADOPT), a modification of ADOPT that changes the search strategy of ADOPT from performing one best-first search to performing a series of depth-first searches. Each depth-first search is provided with a bound, initially a large integer, and returns the first solution whose cost is smaller than or equal to the bound. The bound is then reduced to the cost of this solution minus one and the process repeats. If there is no solution whose cost is smaller than or equal to the bound, it returns a cost-minimal solution. Thus, IDB-ADOPT is an anytime algorithm that solves DCOP problems with integer costs optimally. Our experimental results for graph coloring problems show that IDB-ADOPT runs faster (that is, needs fewer cycles) than ADOPT on large DCOP problems, with savings of up to one order of magnitude.

AB - Many agent coordination problems can be modeled as distributed constraint optimization (DCOP) problems. ADOPT is an asynchronous and distributed search algorithm that is able to solve DCOP problems optimally. In this paper, we introduce Iterative Decreasing Bound ADOPT (IDB-ADOPT), a modification of ADOPT that changes the search strategy of ADOPT from performing one best-first search to performing a series of depth-first searches. Each depth-first search is provided with a bound, initially a large integer, and returns the first solution whose cost is smaller than or equal to the bound. The bound is then reduced to the cost of this solution minus one and the process repeats. If there is no solution whose cost is smaller than or equal to the bound, it returns a cost-minimal solution. Thus, IDB-ADOPT is an anytime algorithm that solves DCOP problems with integer costs optimally. Our experimental results for graph coloring problems show that IDB-ADOPT runs faster (that is, needs fewer cycles) than ADOPT on large DCOP problems, with savings of up to one order of magnitude.

KW - ADOPT

KW - DCOP

KW - Distributed Constraint Optimization

KW - Distributed Search Algorithms

UR - http://www.scopus.com/inward/record.url?scp=69949115583&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-03251-6_9

DO - 10.1007/978-3-642-03251-6_9

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:69949115583

SN - 3642032508

SN - 9783642032509

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 132

EP - 146

BT - Recent Advances in Constraints - 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008, Revised Selected Papers

Y2 - 18 June 2008 through 20 June 2008

ER -

Yeoh W, Felner A, Koenig S. IDB-ADOPT: A depth-first search DCOP algorithm. In Recent Advances in Constraints - 13th Annual ERCIM International Workshop on Constraint Solving and Constraint Logic Programming, CSCLP 2008, Revised Selected Papers. 2009. p. 132-146. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-03251-6_9

IDB-ADOPT: A depth-first search DCOP algorithm

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this