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Planning Under Uncertainty and Its Applications

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Reasoning, Action and Interaction in AI Theories and Systems

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4155))

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Abstract

Several application domains require planning techniques that model uncertainty in the results of both actions and observations. Actions may have different effects that cannot be predicted at planning time. Observations may result into uncertainty about the current state of the world. In this paper, we first discuss the problem of planning with uncertainty in action execution and observations. We then discuss how this problem can be relevant to different application domains that represent rather different characteristics, like planning for controlling a robot that has to perform a surveillance task, as well as planning for the automated composition of web services for e-commerce.

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Author information

Authors and Affiliations

  1. ITC-irst, Via Sommarive 18, 38050, Povo - Trento, Italy

    Paolo Traverso

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  1. Paolo Traverso
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Editors and Affiliations

  1. FBK-irst, I-38050, Povo, Trento, Italy

    Oliviero Stock

  2. Dipartimento di Informatica e Sistemistica, Università di Roma “La Sapienza”, Via Salaria 113, Roma,, Italia

    Marco Schaerf

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© 2006 Springer-Verlag Berlin Heidelberg

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Traverso, P. (2006). Planning Under Uncertainty and Its Applications. In: Stock, O., Schaerf, M. (eds) Reasoning, Action and Interaction in AI Theories and Systems. Lecture Notes in Computer Science(), vol 4155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11829263_12

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  • DOI: https://doi.org/10.1007/11829263_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37901-0

  • Online ISBN: 978-3-540-37902-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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