Skip to main content
SpringerLink
Log in

SOCIAL DCOP - Social Choice in Distributed Constraints Optimization

  • Conference paper
Intelligent Distributed Computing V

Part of the book series: Studies in Computational Intelligence ((SCI,volume 382))

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Berbeglia, G., Cordeau, J., Gribkovskaia, I., Laporte, G.: Static pickup and delivery problems: a classification scheme and survey. TOP: An Official Journal of the Spanish Society of Statistics and Operations Research 15(1), 1–31 (2007)

    MathSciNet  MATH  Google Scholar 

  2. Bergson, A.: A reformulation of certain aspects of welfare economics. The Quarterly Journal of Economics 52(2), 310–334 (1938)

    Article  Google Scholar 

  3. Bouveret, S., Lemaître, M.: Computing leximin-optimal solutions in constraint networks. Artif. Intell. 173(2), 343–364 (2009)

    Article  MATH  Google Scholar 

  4. Dalton, H.: The measurement of the inequality of income. The Economic Journal 30, 348–361 (1920)

    Article  Google Scholar 

  5. D’Aspremont, C., Gevers, L.: Equity and the informational basis of collective choice. The Review of Economic Studies 44(2), 199–209 (1977)

    Article  MATH  Google Scholar 

  6. Gershman, A., Meisels, A., Zivan, R.: Asynchronous forward bounding. J. of Artificial Intelligence Research 34, 25–46 (2009)

    MathSciNet  Google Scholar 

  7. Grubshtein, A., Zivan, R., Grinshpoun, T., Meisels, A.: Local search for distributed asymmetric optimization. In: Proc. AAMAS 2010, pp. 1015–1022 (2010)

    Google Scholar 

  8. Junges, R., Bazzan, A.L.C.: Evaluating the performance of dcop algorithms in a real world, dynamic problem. In: Proc. AAMAS 2008, pp. 599–606 (2008)

    Google Scholar 

  9. Kolm, S.C.: Justice et equite. Centre National de la Recherche, Paris (1972)

    Google Scholar 

  10. Lisý, V., Zivan, R., Sycara, K.P., Pechoucek, M.: Deception in networks of mobile sensing agents. In: AAMAS 2010, pp. 1031–1038 (2010)

    Google Scholar 

  11. Maheswaran, R.T., Pearce, J.P., Tambe, M.: Distributed algorithms for DCOP: A graphical-game-based approach. In: Proc. Parallel and Distributed Computing Systems (PDCS), pp. 432–439 (September 2004)

    Google Scholar 

  12. Maheswaran, R.T., Tambe, M., Bowring, E., Pearce, J.P., Varakantham, P.: Taking DCOP to the real world: Efficient complete solutions for distributed multi-event scheduling. In: Proc. AAMAS 2004, New York, pp. 310–317 (2004)

    Google Scholar 

  13. Mamoru, K., Kenjiro, N.: The nash social welfare function. Econometrica 47(2), 423–435 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  14. Meisels, A.: Distributed Search by Constrained Agents: Algorithms, Performance, Communication. Springer, Heidelberg (2007)

    Google Scholar 

  15. Modi, P.J., Shen, W., Tambe, M., Yokoo, M.: ADOPT: asynchronous distributed constraints optimization with quality guarantees. Artificial Intelligence 161(1-2), 149–180 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  16. Ng, Y.-K.: Bentham or bergson? finite sensibility, utility functions and social welfare functions. The Review of Economic Studies 42(4) (1975)

    Google Scholar 

  17. Ottens, B., Faltings, B.: Coordination agent plans trough distributed constraint optimization. In: Proceedings of the Multi Agent Planning Workshop MASPLAN 2008, Sydney, Australia (September 2008)

    Google Scholar 

  18. Pareto, V.: Cours d’economie politique. Librairie Droz, Geneva (1964)

    Google Scholar 

  19. Pigou, A.C.: Wealth and welfare. Macmillan, London (1912)

    Google Scholar 

  20. Sen, A.: Real national income. The Review of Economic Studies 43, 19–39 (1976)

    Article  MATH  Google Scholar 

  21. Sen, A.: The welfare basis of real income comparisons: A survey. Journal of Economic Literature 17(1), 1–45 (1979)

    Google Scholar 

  22. Zhang, W., Xing, Z., Wang, G., Wittenburg, L.: Distributed stochastic search and distributed breakout: properties, comparishon and applications to constraints optimization problems in sensor networks. Artificial Intelligence 161(1-2), 55–88 (2005)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Ben Gurion University of the Negev, P.O.B 653, Be’er Sheva, 84105, Israel

    Arnon Netzer & Amnon Meisels

Authors
  1. Arnon Netzer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amnon Meisels
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Faculty of Technology,Policy andManagement, Intelligent Interactive Dynamic Systems, Section Systems Engineering, Delft University of Technology, Jaffalaan 5, 2628BX, Delft, The Netherlands

    F. M. T. Brazier

  2. D-CIS lab, P.O. Box 90, 2600 AB, Delft, The Netherlands

    Kees Nieuwenhuis  & Gregor Pavlin  & 

  3. Faculty of Technology,Policy andManagement, Section Systems Engineering, Delft University of Technology, Jaffalaan 5, 2628BX, Delft, The Netherlands

    Martijn Warnier

  4. Faculty of Automatics, Computers and Electronics, Software Engineering Department, University of Craiova, Bvd. Decebal Nr. 107, 200440, Craiova, Romania

    Costin Badica

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Netzer, A., Meisels, A. (2011). SOCIAL DCOP - Social Choice in Distributed Constraints Optimization. In: Brazier, F.M.T., Nieuwenhuis, K., Pavlin, G., Warnier, M., Badica, C. (eds) Intelligent Distributed Computing V. Studies in Computational Intelligence, vol 382. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24013-3_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-24013-3_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24012-6

  • Online ISBN: 978-3-642-24013-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation