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Admissibility Proofs for the LCS* Algorithm

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Advances in Artificial Intelligence (IBERAMIA 2000, SBIA 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1952))

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Abstract

Bidirectional search and heuristic search are techniques that improve the performance of a shortest path graph search. Despite many attempts to use both at the same time, this combination had been leading to worse results in average, compared to the classic unidirectional heuristic A* algorithm. In[4], a new graph search algorithm was developed LCS*, that is the first to combine these techniques effectively. LCS* is a generic and simultaneous bidirectional heuristic algorithm which is faster than A* in most domains. This work present formal proofs of the completeness and admissibility of LCS*.

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References

  1. R. Dechter and J. Pearl, Generalized Best-First Search Strategies and the Optimality of A, J. Assoc. Comput. Mach., 32 (1985), pp. 505–536.

    Article  MathSciNet  Google Scholar 

  2. S. Ghosh and A. Mahanti, Bidirectional Heuristic Search with Limited Resources, Information Processing Letters, 40 (1991), pp. 335–340.

    Google Scholar 

  3. P. E. Hart, N. J. Nilsson, and B. Raphael,A Formal Basis for the Heuristic Determination of Minimum Cost Paths, IEEE Transactions on Systems, Science and Cybernetics, SSC-4 (1968), pp. 100–107.

    Google Scholar 

  4. M. Johann, A. Caldwell, A. Kahng, and R. Reis, A New Bidirectional Heu-ristic Shortest Path Search Algorithm. Accepted for publication in the proceedings of the International ICSC Congress on Intelligent Systems and Applications, 2000.

    Google Scholar 

  5. H. Kaindl, G. Kainz, A. Leeb, and H. Smetana, How to Use Limited Memory in Heuristic Search, in Proceedings of the International Joint Conference on Artificial Intelligence, vol. 1, 1995, pp. 236–242.

    Google Scholar 

  6. H. Kaindl, G. Kainz, Bidirectional Heuristic Search Reconsidered, in Journal of Artificial Intelligence, vol. 7, 1997, pp. 283–317.

    MathSciNet  Google Scholar 

  7. A. L. Koll and H. Kaindl, Bidirectional Best-First Search with Bounded Error: Summary of Results, in Proceedings of the International Joint Conference on Artificial Intelligence, 1993, pp. 217–223.

    Google Scholar 

  8. J. B. H. Kwa, BS: An Admissible Bidirectional Staged Heuristic Search Algo-rithm, Artificial Intelligence, 38 (1989), pp. 95–109.

    Article  MathSciNet  Google Scholar 

  9. G. Manzini, BIDA: An Improved Perimeter Search Algorithm, Artificial Intelligence, 75 (1995), pp. 347–360.

    Article  MathSciNet  Google Scholar 

  10. N. J. Nilsson, Problem-Solving Methods in Artificial Intelligence, McGraw-Hill Book Co., 1971, ch. State-Space Search Methods, pp. 43–79.

    Google Scholar 

  11. J. Pearl, Heuristics, Addison-Wesley, 1984, ch. Formal Properties of Heuristic Methods, pp. 73–87+.

    Google Scholar 

  12. I. Pohl, Bi-Directional Search, in Machine Intelligence, 1971, pp. 127–140.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Federal University of Rio Grande do Sul (UFRGS), Brazil

    Marcelo O. Johann & Ricardo A. L. Reis

  2. University of California at Los Angeles (UCLA), USA

    Andrew Caldwell & Andrew B. Kahng

Authors
  1. Marcelo O. Johann
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  2. Andrew Caldwell
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  3. Ricardo A. L. Reis
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  4. Andrew B. Kahng
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Statistics Computational Intelligence Laboratory, University of São Paulo, Avenida Trabalhador Sãocarlense 400, 13566-590, São Carlos, Brazil

    Maria Carolina Monard

  2. Computer Engineering Department Intelligent Techniques Laboratory, University of São Paulo, Av. Prof. Luciano Gualberto, 158, tv. 3, 05508-900, São Paulo, Brazil

    Jaime Simão Sichman

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© 2000 Springer-Verlag Berlin Heidelberg

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Johann, M.O., Caldwell, A., Reis, R.A.L., Kahng, A.B. (2000). Admissibility Proofs for the LCS* Algorithm. In: Monard, M.C., Sichman, J.S. (eds) Advances in Artificial Intelligence. IBERAMIA SBIA 2000 2000. Lecture Notes in Computer Science(), vol 1952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44399-1_25

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  • DOI: https://doi.org/10.1007/3-540-44399-1_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41276-2

  • Online ISBN: 978-3-540-44399-5

  • eBook Packages: Springer Book Archive

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