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A review of generalized planning

Published online by Cambridge University Press:  12 March 2019

Sergio Jiménez ,
Javier Segovia-Aguas  and
Anders Jonsson
Sergio Jiménez
Affiliation:
Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València, Camino de Vera s/n. 46022 Valencia, Spain e-mail: serjice@dsic.upv.es
Javier Segovia-Aguas
Affiliation:
Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, 08018 Barcelona, Spain e-mail: javier.segovia@upf.edu, anders.jonsson@upf.edu
Anders Jonsson
Affiliation:
Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, 08018 Barcelona, Spain e-mail: javier.segovia@upf.edu, anders.jonsson@upf.edu
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Abstract

Generalized planning studies the representation, computation and evaluation of solutions that are valid for multiple planning instances. These are topics studied since the early days of AI. However, in recent years, we are experiencing the appearance of novel formalisms to compactly represent generalized planning tasks, the solutions to these tasks (called generalized plans) and efficient algorithms to compute generalized plans. The paper reviews recent advances in generalized planning and relates them to existing planning formalisms, such as planning with domain control knowledge and approaches for planning under uncertainty, that also aim at generality.

Type
Review
Information
The Knowledge Engineering Review , Volume 34 , 2019 , e5
Copyright
© Cambridge University Press, 2019 

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