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PC-SHOP: a probabilstic-conditional hierarchical task planner
Örebro University, Department of Technology. (Mobile Robotics Lab)
Örebro University, Department of Technology. (Mobile Robotics Lab)ORCID iD: 0000-0002-0458-2146
2005 (English)In: Intelligenza Artificiale, ISSN 1724-8035, Vol. 2, no 4, p. 44-50Article in journal (Refereed) Published
Abstract [en]

In this paper we report on the extension of the classical HTN planner SHOP to plan in partially observable domains with uncertainty. Our algorithm PC-SHOP uses belief states to handle situations involving incomplete and uncertain information about the state of the world. Sensing and acting are integrated in the primitive actions through the use of a stochastic model. PC-SHOP is showed to scale up well compared to some of the state-of-the-art planners. We outline the main characteristics of the algorithm, and present performance results on some problems found in the literature.

Place, publisher, year, edition, pages
2005. Vol. 2, no 4, p. 44-50
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-3634OAI: oai:DiVA.org:oru-3634DiVA, id: diva2:137932
Available from: 2007-07-29 Created: 2007-07-29 Last updated: 2018-01-13Bibliographically approved

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Bouguerra, AbdelKarlsson, Lars

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