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Boosting distributed constraint satisfaction

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Abstract

Competition and cooperation can boost the performance of a combinatorial search process. Both can be implemented with a portfolio of algorithms which run in parallel, give hints to each other and compete for being the first to finish and deliver the solution. In this paper we present a new generic framework for the application of algorithms for distributed constraint satisfaction that makes use of both cooperation and competition. This framework improves the performance of two different standard algorithms by one order of magnitude. Furthermore, it can reduce the risk of poor performance by up to three orders of magnitude diminishing the heavy-tailed behaviour of complete distributed search. Moreover it greatly reduces the classical idleness flaw usually observed in distributed tree-based searches. We expect our new methods to be similarly beneficial for any tree-based distributed search and describe ways on how to incorporate them. Remarkably, our ideas while applied to a parallel SAT setting were able to beat divide-and-conquers approaches, and win the gold medal of the parallel track of the 2008 SAT-Race.

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References

  • Armstrong, A., Durfee, E.: Dynamic prioritization of complex agents in distributed constraint satisfaction problems. In: Proc. of the 15th Int. Joint Conf. on AI (IJCAI-97), pp. 620–625 (1997)

  • Bessiere, C., Regin, J.C.: Mac and combined heuristics: Two reasons to forsake FC (and CBJ?) on hard problems. In: CP, pp. 61–75 (1996)

  • Bessiere, C., Brito, I., Maestre, A., Meseguer, P.: Asynchronous backtracking without adding links: A new member in the ABT family. Artif. Intel. 161, 7–24 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  • Bordeaux, L., Hamadi, Y., Zhang, L.: Propositional satisfiability and constraint programming: A comparative survey. ACM Comput. Surv. 38(4) (2006)

  • Buchanan, B.G.: What do we know about knowledge? AI Mag. 27(4), 35–46 (2006)

    Google Scholar 

  • Carchrae, T., Beck, J.C.: Low knowledge algorithm control. In: Proc. AAAI’04 (2004)

  • Chandy, K.M., Lamport, L.: Distributed snapshots: Determining global states of distributed systems. ACM Trans. Comput. Syst. 3(1), 63–75 (1985)

    Article  Google Scholar 

  • Fitzpatrick, S., Meertens, L.: Scalable, anytime constraint optimization through iterated, peer-to-peer interaction in sparsely-connected networks. In: Proc. IDPT’02 (2002)

  • Gent, I., Walsh, T.: CSPLib, a problem library for constraints, http://www-users.cs.york.ac.uk/tw/csplib/

  • Gershman, A., Zivan, R., Grinshpoun, T., Meisels, A.: Measuring distributed constraint optimization algorithms. In: AAMAS DCR (2008)

  • Gomes, C.: Randomized backtrack search. In: Milano, M. (ed.) Constraint and Integer Programming: Toward a Unified Methodology, pp. 233–283. Kluwer, Dordrecht (2003)

    Google Scholar 

  • Gomes, C., Selman, B.: Algorithm portfolio design: Theory vs. practice. In: Proc. UAI’97, pp. 190–197 (1997)

  • Gomes, C., Selman, B.: Algorithm portfolios. Artif. Intel. 126, 43–62 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  • Gomes, C., Selman, B., Kautz, H.: Boosting combinatorial search through randomization. In: Proc. AAAI’98, pp. 431–438. AAAI Press, Menlo Park (1998)

    Google Scholar 

  • Greenstadt, R., Grosz, B.J., Smith, M.D.: Ssdpop: Improving the privacy of dcop with secret sharing. In: AAMAS, p. 171 (2007)

  • Hamadi, Y.: Optimal distributed arc-consistency. In: Proc. CP’99, pp. 219–233 (1999)

  • Hamadi, Y.: Interleaved backtracking in distributed constraint networks. Int. J. Artif. Intel. Tools 11(2), 167–188 (2002)

    Article  Google Scholar 

  • Hamadi, Y., Bessiere, C., Quinqueton, J.: Backtracking in distributed constraint networks. In: Proc. ECAI’98, pp. 219–223 (1998)

  • Hamadi, Y., Jabbour, S., Sais, L.: Manysat: Solver description. Tech. rep. MSR-TR-2008-83, Microsoft Research (2008)

  • Hamadi, Y., Jabbour, S., Sais, L.: ManySAT: A parallel SAT solver. J. Satisf. Boolean Model. Comput. 6, 245–262 (2009)

    MATH  Google Scholar 

  • Hill, B.: A simple general approach to inference about the tail of a distribution. Ann. Stat. 1163–1174 (1975)

  • Hogg, T., Huberman, B.A.: Better than the best: The power of cooperation. In: 1992 Lectures in Complex Systems. SFI Studies in the Sciences of Complexity, vol. 5, pp. 165–184. Addison-Wesley, Reading (1993)

    Google Scholar 

  • Lamport, L.: Time, clocks and the ordering of events in distributed systems. Commun. ACM 2, 95–104 (1978)

    MathSciNet  Google Scholar 

  • Leyton-Brown, K., Nudelman, E., Andrew, G., McFadden, J., Shoham, Y.: A portfolio approach to algorithm selection. In: Proc. IJCAI’03, p. 1542 (2003)

  • Modi, P.J., Shen, W.-M., Tambe, M., Yokoo, M..: Adopt: Asynchronous distributed constraint optimization with quality guarantees. Artif. Intel. 161 (2005)

  • Otten, L., Grönkvist, M., Dubhashi, D.P.: Randomization in constraint programming for airline planning. In: CP, pp. 406–420 (2006)

  • Puget, J.F.: Some challenges for constraint programming: an industry view. In: Proc. CP’04, Invited Talk. LNCS, vol. 3258, pp. 5–9. Springer, Berlin (2004)

    Google Scholar 

  • Rice, J.R.: The algorithm selection problem. Adv. Comput. 15, 65–118 (1976)

    Article  Google Scholar 

  • Ringwelski, G., Hamadi, Y.: Boosting distributed constraint satisfaction. In: Beek, P. (ed.): Principles and Practice of Constraint Programming. LNCS, vol. 3709, pp. 549–562. Springer, Berlin (2005)

    Chapter  Google Scholar 

  • Silaghi, M.-C., Faltings, B.: Asynchronous aggregation and consistency in distributed constraint satisfaction. Artif. Intel. 161 (2005)

  • Silaghi, M.-C., Sam-Haroud, D., Faltings, B.: Asynchronous search with aggregations. In: Proc. AAAI/IAAI 2000, pp. 917–922 (2000)

  • Silaghi, M., Lass, R., Sultanik, E., Regli, W., Matsui, T., Yokoo, M.: The operation point units of distributed constraint solvers. In: AAMAS DCR (2008)

  • Xu, L., Hutter, F., Hoos, H.H., Leyton-Brown, K.: The design and analysis of an algorithm portfolio for sat. In: CP, pp. 712–727 (2007)

  • Yokoo, M., Durfee, E.H.: The distributed constraint satisfaction problem: Formalization and algorithms. IEEE Trans. Knowl. Data Eng. 10(5) (1998)

  • Yokoo, M., Durfee, E.H., Ishida, T., Kuwabara, K.: Distributed constraint satisfaction for formalizing distributed problem solving. In: Proc. ICDCS’92, pp. 614–621 (1992)

  • Zivan, R., Meisels, A.: Synchronous vs asynchronous search on DisCSPs. In: Proc. EUMAS’03 (2003)

  • Zivan, R., Meisels, A.: Concurrent search for distributed csps. Artif. Intel. 161 (2005)

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Authors and Affiliations

  1. Microsoft Research, 7 J J Thomson Avenue, Cambridge, CB3 0FB, UK

    Youssef Hamadi

  2. LIX École Polytechnique, 91128, Palaiseau, France

    Youssef Hamadi

  3. Fachbereich Informatik, Hochschule Zittau/Görlitz, Brückenstraße 1, 02826, Görlitz, Germany

    Georg Ringwelski

Authors
  1. Youssef Hamadi
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  2. Georg Ringwelski
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Correspondence to Youssef Hamadi.

Additional information

This work has received support from the Embark Initiative of the Irish Research Council of Science Engineering and Technology under Grant PD2002/21.

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Hamadi, Y., Ringwelski, G. Boosting distributed constraint satisfaction. J Heuristics 17, 251–279 (2011). https://doi.org/10.1007/s10732-010-9134-2

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  • DOI: https://doi.org/10.1007/s10732-010-9134-2

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