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A motivation-based planning and execution framework

Coddington, A.M. and Luck, M. (2004) A motivation-based planning and execution framework. International Journal on Artificial Intelligence Tools, 13 (1). pp. 5-25. ISSN 0218-2130

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AI planning systems tend to be disembodied and are not situated within the environment for which plans are generated, thus losing information concerning the interaction between the system and its environment. This paper argues that such information may potentially be valuable in constraining plan formulation, and presents both an agent- and domain-independent architecture that extends the classical AI planning framework to take into account context, or the interaction between an autonomous situated planning agent and its environment. The paper describes how context constrains the goals an agent might generate, enables those goals to be prioritised, and constrains plan selection.

Item type: Article
ID code: 1928
Keywords: AI planning, agent architectures, motivations, plan evaluation, Electronic computers. Computer science, Artificial Intelligence
Subjects: Science > Mathematics > Electronic computers. Computer science
Department: Faculty of Science > Computer and Information Sciences
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    Depositing user: Strathprints Administrator
    Date Deposited: 27 Oct 2006
    Last modified: 04 Sep 2014 12:10

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