SOCIAL DCOP - Social choice in distributed constraints optimization

Arnon Netzer; Amnon Meisels

doi:10.1007/978-3-642-24013-3_5

SOCIAL DCOP - Social choice in distributed constraints optimization

Arnon Netzer
, Amnon Meisels

Ben-Gurion University of the Negev

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

7 Scopus citations

Abstract

Distributed Social Constraints Optimization Problems (DSCOPs) are DCOPs in which the global objective function for optimization incorporates a social welfare function (SWF). DSCOPs have individual, non-binary and asymmetric constraints and thus form a unique DCOP class. DSCOPs provide a natural framework for agents that compute their costs individually and are therefore self-interested. The concept of social welfare is discussed and SWFs are presented. An important aspect of DSCOPs and of social objective functions is their ability to support distributed hill climbing algorithms. The DSCOP hill climbing algorithm is presented and tested experimentally on multi agent pickup and delivery problems. It turns out to improve the distribution of utility gains among agents, while loosing very little in global gain.

Original language	English
Title of host publication	Intelligent Distributed Computing V
Subtitle of host publication	Proceedings of the 5th International Symposium on Intelligent Distributed Computing - IDC 2011, Delft, The Netherlands - October 2011
Editors	Frances M.T. Brazier, Kees Nieuwenhuis, Gregor Pavlin, Martijn Warnier, Costin Badica
Pages	35-47
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-642-24013-3_5
State	Published - 2011
Externally published	Yes

Publication series

Name	Studies in Computational Intelligence
Volume	382
ISSN (Print)	1860-949X

Access to Document

10.1007/978-3-642-24013-3_5

Cite this

Netzer, A., & Meisels, A. (2011). SOCIAL DCOP - Social choice in distributed constraints optimization. In F. M. T. Brazier, K. Nieuwenhuis, G. Pavlin, M. Warnier, & C. Badica (Eds.), Intelligent Distributed Computing V: Proceedings of the 5th International Symposium on Intelligent Distributed Computing - IDC 2011, Delft, The Netherlands - October 2011 (pp. 35-47). (Studies in Computational Intelligence; Vol. 382). https://doi.org/10.1007/978-3-642-24013-3_5

Netzer, Arnon ; Meisels, Amnon. / SOCIAL DCOP - Social choice in distributed constraints optimization. Intelligent Distributed Computing V: Proceedings of the 5th International Symposium on Intelligent Distributed Computing - IDC 2011, Delft, The Netherlands - October 2011. editor / Frances M.T. Brazier ; Kees Nieuwenhuis ; Gregor Pavlin ; Martijn Warnier ; Costin Badica. 2011. pp. 35-47 (Studies in Computational Intelligence).

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abstract = "Distributed Social Constraints Optimization Problems (DSCOPs) are DCOPs in which the global objective function for optimization incorporates a social welfare function (SWF). DSCOPs have individual, non-binary and asymmetric constraints and thus form a unique DCOP class. DSCOPs provide a natural framework for agents that compute their costs individually and are therefore self-interested. The concept of social welfare is discussed and SWFs are presented. An important aspect of DSCOPs and of social objective functions is their ability to support distributed hill climbing algorithms. The DSCOP hill climbing algorithm is presented and tested experimentally on multi agent pickup and delivery problems. It turns out to improve the distribution of utility gains among agents, while loosing very little in global gain.",

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Netzer, A & Meisels, A 2011, SOCIAL DCOP - Social choice in distributed constraints optimization. in FMT Brazier, K Nieuwenhuis, G Pavlin, M Warnier & C Badica (eds), Intelligent Distributed Computing V: Proceedings of the 5th International Symposium on Intelligent Distributed Computing - IDC 2011, Delft, The Netherlands - October 2011. Studies in Computational Intelligence, vol. 382, pp. 35-47. https://doi.org/10.1007/978-3-642-24013-3_5

SOCIAL DCOP - Social choice in distributed constraints optimization. / Netzer, Arnon; Meisels, Amnon.
Intelligent Distributed Computing V: Proceedings of the 5th International Symposium on Intelligent Distributed Computing - IDC 2011, Delft, The Netherlands - October 2011. ed. / Frances M.T. Brazier; Kees Nieuwenhuis; Gregor Pavlin; Martijn Warnier; Costin Badica. 2011. p. 35-47 (Studies in Computational Intelligence; Vol. 382).

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

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AB - Distributed Social Constraints Optimization Problems (DSCOPs) are DCOPs in which the global objective function for optimization incorporates a social welfare function (SWF). DSCOPs have individual, non-binary and asymmetric constraints and thus form a unique DCOP class. DSCOPs provide a natural framework for agents that compute their costs individually and are therefore self-interested. The concept of social welfare is discussed and SWFs are presented. An important aspect of DSCOPs and of social objective functions is their ability to support distributed hill climbing algorithms. The DSCOP hill climbing algorithm is presented and tested experimentally on multi agent pickup and delivery problems. It turns out to improve the distribution of utility gains among agents, while loosing very little in global gain.

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Netzer A, Meisels A. SOCIAL DCOP - Social choice in distributed constraints optimization. In Brazier FMT, Nieuwenhuis K, Pavlin G, Warnier M, Badica C, editors, Intelligent Distributed Computing V: Proceedings of the 5th International Symposium on Intelligent Distributed Computing - IDC 2011, Delft, The Netherlands - October 2011. 2011. p. 35-47. (Studies in Computational Intelligence). doi: 10.1007/978-3-642-24013-3_5

SOCIAL DCOP - Social choice in distributed constraints optimization

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