RT Journal Article
T1 Selecting goals in oversubscription planning using relaxed plans
A1 García Olaya, Ángel
A1 De la Rosa Turbides, Tomás Eduardo
A1 Borrajo Millán, Daniel
AB Planning deals with the task of finding an ordered set of actions that achieves some goals from an initial state. In many real-world applications it is unfeasible to find a plan achieving all goals due to limitations in the available resources. A common case consists of having a bound on a given cost measure that is less than the optimal cost needed to achieve all goals. Oversubscription planning (OSP) is the field of Automated Planning dealing with such kinds of problems. Usually, OSP generates plans that achieve only a subset of the goals set. In this paper we present a new technique to a priori select goals in no-hard-goals satisficing OSP by searching in the space of subsets of goals. A key property of the proposed approach is that it is planner-independent once the goals have been selected; it creates a new non-OSP problem that can be solved using off-the-shelf planners. Extensive experimental results show that the proposed approach outperforms state-of-the-art OSP techniques in several domains of the International Planning Competition.
PB Elsevier
SN 0004-3702
YR 2021
FD 2021-02-01
LK https://hdl.handle.net/10016/34506
UL https://hdl.handle.net/10016/34506
LA eng
NO This work has been partially funded by the European Union ECHORD++ project (FP7-ICT-601116), by FEDER/Ministerio de Ciencia, Innovación y Universidades/Agencia Estatal de Investigación TIN2017-88476-C2-2-R, RTC-2016-5407-4 and RTI2018-099522-B-C43 projects and the ESA GOTCHA project (4000117648/16/NL/GLC/fk). We would like to thank Michael Katz, Daniel Muller and Nir Lipovetzky for supporting us in using their planners and the reviewers for their helpful comments.
DS e-Archivo
RD 2 may. 2024