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Brazilian Symposium on Artificial Intelligence

SBIA 1996: Advances in Artificial Intelligence pp 41–50Cite as

Algorithms ϱ for ℒ-standard state graphs: Results about termination and admissibility

  • Planning, Learning and Heuristic Search
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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1159))

Abstract

We formally extend various works dealing with Heuristic Search in state graphs, focusing on 1) the notion of path length, 2) the characteristics of the state graphs, 3) the procedures that control the choices of the states to be expanded, 4) the rules that govern the update operations, 5) the properties of the evaluation functions. We present new general theorems concerning the termination at a goal state, the admissibility and the sub-admissibility.

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References

  1. A. Bagchi and A. Mahanti, Three approaches to heuristic search in networks, J. ACM 32 (1) (1985) 1–27.

    Google Scholar 

  2. R. Dechter and J. Pearl, The optimality of A*, in: L. Kanal and D. Kumar, eds, Search in Artificial Intelligence (Springer-Verlag, 1988) 166–199.

    Google Scholar 

  3. H. Farreny, Recherche Heuristiquement Ordonnée — Algorithmes et propriétés, (Masson, Paris, 1995).

    Google Scholar 

  4. H. Farreny, Une généralisation pour la Recherche Heuristiquement Ordonnée: les algorithmes ϱ et la propriété d'arrêt avec découverte de solution, in: Proc. of RFIA 96, Rennes, France (1996) 225–234.

    Google Scholar 

  5. M. Ghallab and D. G. Allard, Ag: An efficient near admissible heuristic search algorithm, in: Proc. 8th IJCAI, Karlsruhe, Germany (1983) 789–791.

    Google Scholar 

  6. L. R. Harris, The heuristic search under conditions of error, Art. Int. 5 (3) (1974) 217–234.

    Google Scholar 

  7. A. Köll L. and H. Kaindl, A new approach to dynamic weighting, in: Proc. 10th ECAI, Vienna, Austria (1992) 16–17.

    Google Scholar 

  8. R. E. Korf, Depth-first iterative-deepening: an optimal admissible tree search, Art. Int. 27 (1985) 97–109.

    Google Scholar 

  9. A. Mahanti and K. Ray, Network search algorithms with modifiable heuristics, in: L. Kanal and D. Kumar, eds, Search in Art. Int., (Springer-Verlag, 1988) 200–222.

    Google Scholar 

  10. A. Martelli, On the complexity of admissible search algorithms, Art. Int. 8 (1) (1977) 1–13.

    Google Scholar 

  11. L. Mero, A heuristic search algorithm with modifiable estimate, Art. Int. 23 (1) (1984) 13–27.

    Google Scholar 

  12. N. J. Nilsson, Problem-solving methods in artificial intelligence, (Mc Graw-Hill, 1971).

    Google Scholar 

  13. N. J. Nilsson, Principles of artificial intelligence, (Tioga, 1980).

    Google Scholar 

  14. J. Pearl, Heuristics: intelligent search strategies for computer problem solving (Addison-Wesley, 1984).

    Google Scholar 

  15. I. Pohl, The avoidance of (relative) catastrophe, heuristic competence, genuine dynamic weighting and computational issues in heuristic problem solving, in: Proc. 3d IJCAI, Stanford, USA (1973) 12–17.

    Google Scholar 

  16. I. Pohl, Practical and theoretical considerations in heuristic search algorithms, in: E. W. Elcock and D. Michie, eds, Machine Intelligence 8 (Wiley, 1977) 55–71.

    Google Scholar 

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Author information

Authors and Affiliations

  1. IRIT, 118 Route de Narbonne, 31 062, Toulouse cédex, France

    Henri Farreny

Authors
  1. Henri Farreny
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Editor information

Díbio L. Borges Celso A. A. Kaestner

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© 1996 Springer-Verlag Berlin Heidelberg

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Farreny, H. (1996). Algorithms ϱ for ℒ-standard state graphs: Results about termination and admissibility. In: Borges, D.L., Kaestner, C.A.A. (eds) Advances in Artificial Intelligence. SBIA 1996. Lecture Notes in Computer Science, vol 1159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61859-7_5

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  • DOI: https://doi.org/10.1007/3-540-61859-7_5

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61859-1

  • Online ISBN: 978-3-540-70742-4

  • eBook Packages: Springer Book Archive

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