Picture of aircraft jet engine

Strathclyde research that powers aerospace engineering...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by Strathclyde researchers involved in aerospace engineering and from the Advanced Space Concepts Laboratory - but also other internationally significant research from within the Department of Mechanical & Aerospace Engineering. Discover why Strathclyde is powering international aerospace research...

Strathprints also exposes world leading research from the Faculties of Science, Engineering, Humanities & Social Sciences, and from the Strathclyde Business School.

Discover more...

Forward-chaining partial-order planning

Coles, A. J. and Coles, A. I. and Fox, M. and Long, D. (2010) Forward-chaining partial-order planning. In: Proceedings of the 20th international conference on automated planning and scheduling, ICAPS 2010. AAAI Press, Palo Alto. ISBN 9781577354499

[img]
Preview
PDF
strath_cis_publication_2437.pdf - Accepted Author Manuscript

Download (213kB) | Preview

Abstract

Over the last few years there has been a revival of interest in the idea of least-commitment planning with a number of researchers returning to the partial-order planning approaches of UCPOP and VHPOP. In this paper we explore the potential of a forward-chaining state-based search strategy to support partial-order planning in the solution of temporal-numeric problems. Our planner, POPF, is built on the foundations of grounded forward search, in combination with linear programming to handle continuous linear numeric change. To achieve a partial ordering we delay commitment to ordering decisions, timestamps and the values of numeric parameters, managing sets of constraints as actions are started and ended. In the context of a partially ordered collection of actions, constructing the linear program is complicated and we propose an efficient method for achieving this. Our late-commitment approach achieves flexibility, while benefiting from the informative search control of forward planning, and allows temporal and metric decisions to be made - as is most efficient - by the LP solver rather than by the discrete reasoning of the planner. We compare POPF with the approach of constructing a sequenced plan and then lifting a partial order from it, showing that our approach can offer improvements in terms of makespan, and time to find a solution, in several benchmark domains.