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Model-Based Search

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Abstraction, Reformulation and Approximation (SARA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3607))

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Abstract

I am interested in heuristic search and optimization, particularly algorithms that explicitly construct a model of the search space and attempt rational action with respect to this abstract model.

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References

  1. Ruml, W.: Incomplete tree search using adaptive probing. In: Proceedings of IJCAI 2001, pp. 235–241 (2001)

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  2. Ruml, W.: Heuristic search in bounded-depth trees: Best-leaf-first search. In: Working Notes of the AAAI 2002 Workshop on Probabilistic Approaches in Search (2002)

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  3. Korf, R.E.: Improved limited discrepancy search. In: Proceedings of AAAI 1996, pp. 286–291. MIT Press, Cambridge (1996)

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  4. Ruml, W.: Adaptive Tree Search. PhD thesis, Harvard University (2002)

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  5. Fang, H., Ruml, W.: Complete local search for propositional satisfiability. In: Proceedings of AAAI 2004 (2004)

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  6. Ruml, W., Crawford, E.: Best-first search when time matters. In: Working Notes of the IJCAI 2005 Workshop on Planning and Learning in A Priori Unknown or Dynamic Domains (2005)

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© 2005 Springer-Verlag Berlin Heidelberg

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Ruml, W. (2005). Model-Based Search. In: Zucker, JD., Saitta, L. (eds) Abstraction, Reformulation and Approximation. SARA 2005. Lecture Notes in Computer Science(), vol 3607. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527862_35

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  • DOI: https://doi.org/10.1007/11527862_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27872-6

  • Online ISBN: 978-3-540-31882-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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