Portfolio-based planning: State of the art, common practice and open challenges

Article type: Research Article

Authors: Vallati, Mauro^{; *} | Chrpa, Lukáš | Kitchin, Diane

Affiliations: School of Computing and Engineering, University of Huddersfield, Huddersfield, West Yorkshire, HD1 3DH, UK. E-mails: [email protected], [email protected], [email protected]

Correspondence: [*] Corresponding author. E-mail: [email protected].

Abstract: In recent years the field of Automated Planning has significantly advanced and several powerful domain-independent planners have been developed. However, none of these systems clearly outperforms all the others in every known benchmark domain. This observation motivated the idea of configuring and exploiting a portfolio of planners to perform better than any individual planner: some recent planning systems based on this idea achieved significantly good results in experimental analysis and International Planning Competitions. Such results let us suppose that future challenges of the Automated Planning community will converge on designing different approaches for combining existing planning algorithms. This paper reviews existing techniques and provides an exhaustive guide to portfolio-based planning. In addition, the paper outlines open issues of existing approaches and highlights possible future evolution of these techniques.

Keywords: Artificial Intelligence, Automated Planning, portfolio approaches

DOI: 10.3233/AIC-150671

Journal: AI Communications, vol. 28, no. 4, pp. 717-733, 2015