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Towards inducing hierarchical task network domain models for AI planning from examples

Richardson, Nona Elizabeth (2006) Towards inducing hierarchical task network domain models for AI planning from examples. In: Proceedings of Computing and Engineering Annual Researchers' Conference 2006: CEARC’06. University of Huddersfield, Huddersfield, pp. 1-5.

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    Abstract

    Domain modelling for AI Planning aims to form a database of facts about the ‘world’ being modelled.
    This can be a complex process especially if there is a large number of objects or actions or both to be
    modelled. This task can be facilitated by tools which induce operators or methods from examples.
    Further, large and complex domains are more easily constructed if domain languages are used which
    allow for hierarchical decomposition of domain components. Examples of such a decomposition are
    class hierarchies and method hierarchies. This paper describes ongoing work which aims to
    produce algorithms which learn effective hierarchical decompositions from examples.

    Item Type: Book Chapter
    Uncontrolled Keywords: domain model, operators, methods, GIPO
    Subjects: T Technology > T Technology (General)
    Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Schools: School of Computing and Engineering
    School of Computing and Engineering > Computing and Engineering Annual Researchers' Conference (CEARC)
    Related URLs:
    Depositing User: Graham Stone
    Date Deposited: 03 Apr 2009 11:44
    Last Modified: 28 Jul 2010 19:32
    URI: http://eprints.hud.ac.uk/id/eprint/3801

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