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Please use this identifier to cite or link to this item: http://hdl.handle.net/10016/6770

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Title: Integrating planning and learning: the prodigy architecture
Author(s): Veloso, Manuela
Carbonel, Jaime
Pérez, Alicia
Borrajo, Daniel
Fink, Eugene
Blythe, Jim
Publisher: Taylor & Francis
Issued date: 1995
Citation: Journal of experimental and theoretical Artificial intelligence, 1995, vol. 7, p. 81-120
URI: http://hdl.handle.net/10016/6770
ISSN: 1362-3079 (online)
0952-813X (print)
Abstract: Planning is a complex reasoning task that is well suited for the study of improving performance and knowledge by learning, i.e. by accumulation and interpretation of planning experience. PRODIGY is an architecture that integrates planning with multiple learning mechanisms. Learning occurs at the planner’s decision points and integration in PRODIGY is achieved via mutually interpretable knowledge structures. This article describes the PRODIGY planner, briefly reports on several learning modules developed earlier along the project, and present sin more detail two recently explored methods to learn to generate plans of better quality. We introduce the techniques, illustrate them with comprehensive examples, and show preliminary empirical results. The article also includes a retrospective discussion of the characteristics of the overall PRODIGY architecture and discusses their evolution with in the goal of the project of building a large and robust integrated planning and learning system.
Review: PeerReviewed
Publisher version: http://eprints.kfupm.edu.sa/46338/1/46338.pdf
Rights: © Taylor & Francis
Appears in Collections:DI - PLG - Artículos de Revistas

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