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A Global Filtration for Satisfying Goals in Mutual Exclusion Networks

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5129))

Abstract

We formulate a problem of goal satisfaction in mutex networks in this paper. The proposed problem is motivated by problems that arise in concurrent planning. For more efficient solving of goal satisfaction problem we design a novel global filtration technique. The filtration technique is based on exploiting graphical structures of the problem - clique decomposition of the problem is used. We evaluated the proposed filtration technique on a set of random goal satisfaction problems as well as a part of GraphPlan based planning algorithm. In both cases we obtained significant improvements in comparison with existing techniques.

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References

  1. Allen, J., Hendler, J., Tate, A.: Readings in Planning. Morgan Kaufmann Publishers, San Francisco (1990)

    Google Scholar 

  2. Blum, A.L., Furst, M.L.: Fast Planning through planning graph analysis. Artificial Intelligence 90, 281–300 (1997)

    Article  MATH  Google Scholar 

  3. Cook, S.A.: The Complexity of Theorem Proving Procedures. In: Proceedings of the 3rd Annual ACM Symposium on Theory of Computing, pp. 151–158. ACM Press, USA (1971)

    Google Scholar 

  4. Dechter, R.: Constraint Processing. Morgan Kaufmann Publishers, San Francisco (2003)

    MATH  Google Scholar 

  5. Golumbic, M.C.: Algorithmic Graph Theory and Perfect Graphs. Academic Press, London (1980)

    MATH  Google Scholar 

  6. Kambhampati, S.: Planning Graph as a (Dynamic) CSP: Exploiting EBL, DDB and other CSP Search Techniques in Graphplan. JAIR 12, 1–34 (2000)

    MATH  Google Scholar 

  7. Kambhampati, S., Parker, E., Lambrecht, E.: Understanding and Extending GraphPlan. In: Steel, S. (ed.) ECP 1997. LNCS, vol. 1348, pp. 260–272. Springer, Heidelberg (1997)

    Chapter  Google Scholar 

  8. Koehler, J.: Homepage of IPP. Research web page University of Freiburg, Germany (April 2007), http://www.informatik.uni-freiburg.de/~koehler/ipp.html

  9. Little, I., Thiébaux, S.: Concurrent Probabilistic Planning in the Graphplan Framework. In: Proceedings of the 16th International Conference on Automated Planning and Scheduling, Cumbria, UK, pp. 263–272. AAAI Press, Menlo Park (2006)

    Google Scholar 

  10. Long, D., Fox, M.: Efficient Implementation of the Plan Graph in STAN. JAIR 10, 87–115 (1999)

    MATH  Google Scholar 

  11. Mackworth, A.K.: Consistency in Networks of Relations. Artificial Intelligence 8, 99–118 (1977)

    Article  MATH  Google Scholar 

  12. Régin, J.C.: A Filtering Algorithm for Constraints of Difference. In: Proceedings of the 12th National Conference on Artificial Intelligence, pp. 362–367. AAAI Press, Menlo Park (1994)

    Google Scholar 

  13. Surynek, P.: Tractable Class of a Problem of Goal Satisfaction in Mutual Exclusion Network. In: Proceedings of the 21st International FLAIRS Conference, Miami, FL, USA. AAAI Press, Menlo Park (to appear, 2008)

    Google Scholar 

  14. Surynek, P.: Projection Global Consistency: An Application in AI Planning. Technical Report, ITI Series, 2007-333. Charles University, Prague (2007), http://iti.mff.cuni.cz/series

  15. Surynek, P.: Projection Global Consistency: An Application in AI Planning. In: Proceedings of CSCLP Workshop 2007, France, INRIA, pp. 61–75 (2007)

    Google Scholar 

  16. Surynek, P., Barták, R.: Maintaining Arc-consistency over Mutex Relations in Planning Graphs during Search. In: Proceedings of the 20th International FLAIRS Conference, Key West, FL, USA, pp. 134–139. AAAI Press, Menlo Park (2007)

    Google Scholar 

  17. Surynek, P.: Solving Difficult SAT Instances Using Greedy Clique Decomposition. In: Miguel, I., Ruml, W. (eds.) SARA 2007. LNCS (LNAI), vol. 4612, pp. 359–374. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  18. Surynek, P., Chrpa, L., Vyskočil, J.: Solving Difficult Problems by Viewing Them as Structured Dense Graphs. In: Proceedings of the 3rd IICAI Conference, Pune, India (2007)

    Google Scholar 

  19. Urquhart, A.: Hard Examples for Resolution. Journal of the ACM 34, 209–219 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  20. Zimmerman, T., Kambhampati, S.: Using Memory to Transform Search on the Planning Graph. JAIR 23, 533–585 (2005)

    MATH  Google Scholar 

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Surynek, P. (2008). A Global Filtration for Satisfying Goals in Mutual Exclusion Networks. In: Fages, F., Rossi, F., Soliman, S. (eds) Recent Advances in Constraints. CSCLP 2007. Lecture Notes in Computer Science(), vol 5129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89812-2_10

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  • DOI: https://doi.org/10.1007/978-3-540-89812-2_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89811-5

  • Online ISBN: 978-3-540-89812-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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