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International Workshop on Model Checking and Artificial Intelligence

MoChArt 2010: Model Checking and Artificial Intelligence pp 1–11Cite as

Planning with Incomplete Information

(Invited Paper)

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6572))

Abstract

Planning is concerned with the development of solvers for a wide range of models where actions must be selected for achieving goals. In these models, actions may be deterministic or not, and full or partial sensing may be available. In the last few years, significant progress has been made, resulting in algorithms that can produce plans effectively in a variety of settings. These developments have to do with new formulations, inference techniques, and transformations. In this paper, I review some of these developments, focusing on those pertaining to planning with incomplete information.

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Author information

Authors and Affiliations

  1. ICREA & Universitat Pompeu Fabra, Roc Boronat 138, 08018, Barcelona, Spain

    Hector Geffner

Authors
  1. Hector Geffner
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Editor information

Editors and Affiliations

  1. School of Computer Science and Engineering, University of New South Wales, 2052, Sydney, Australia

    Ron van der Meyden

  2. Institut für Informatik, Albert-Ludwigs-Universität Freiburg, 79110, Freiburg, Germany

    Jan-Georg Smaus

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Geffner, H. (2011). Planning with Incomplete Information. In: van der Meyden, R., Smaus, JG. (eds) Model Checking and Artificial Intelligence. MoChArt 2010. Lecture Notes in Computer Science(), vol 6572. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20674-0_1

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  • DOI: https://doi.org/10.1007/978-3-642-20674-0_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20673-3

  • Online ISBN: 978-3-642-20674-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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