COLIN: Planning with Continuous Linear Numeric Change
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COLIN: Planning with Continuous Linear Numeric Change
Journal of Artificial Intelligence Research 44 (2012) 1-96Submitted 01/12: published 05/12Colin: Planning with Continuous Linear Numeric ChangeAmanda COLIN: Planning with Continuous Linear Numeric Change ColesAMANDA.CO1.ES @KCL. AC.UKAndrew ColesANDREW.COI.ES@-KCL.AC.UKMaria FoxMARIA.FOX@KCL.AC.UKDerek LongDEREK.LONG@KCL.AC.UKDepartment of Informatics. King's College London.Strand. London WC2R 2LS. UKAbstractIn (his paper we describe COLIN, a forward-chaining heuristic search planner, capable of re COLIN: Planning with Continuous Linear Numeric Change asoning with continuous LlNear numeric change, in addition to the full temporal semantics of PDDI.2.1. Through this work wc make two advances to the sCOLIN: Planning with Continuous Linear Numeric Change
tate-of-the-art in terms of expressive reasoning capabilities of planners: the handling of continuous linear change, and the handling of duration-depeJournal of Artificial Intelligence Research 44 (2012) 1-96Submitted 01/12: published 05/12Colin: Planning with Continuous Linear Numeric ChangeAmanda COLIN: Planning with Continuous Linear Numeric Change ombines FF-style forward chaining search, with the use of a Linear Program (LP) to check the consistency of the interacting temporal and numeric conslraints at each state. The LP is used to compute bounds on the values of variables in each state, reducing the range of actions that need to be conside COLIN: Planning with Continuous Linear Numeric Change red for application. In addition, we develop an extension of the Temporal Relaxed Planning Graph heuristic of CRIKEY3, to support reasoning directly wCOLIN: Planning with Continuous Linear Numeric Change
ith continuous change- We extend the range of task variables considered to be suitable candidates for specifying the gradient of the continuous numerJournal of Artificial Intelligence Research 44 (2012) 1-96Submitted 01/12: published 05/12Colin: Planning with Continuous Linear Numeric ChangeAmanda COLIN: Planning with Continuous Linear Numeric Change the actions in the plan, once a solution has been found. To support this, we further contribute a selection of extended benchmaik domains that include continuous numeric effects. We present results for cot.IN that demonstrate its scalability on a range of benchmarks, and compare to existing state-of COLIN: Planning with Continuous Linear Numeric Change -the-art planners.1IntroductionThere has been considerable progress in the development of automated planning techniques for domains involving independCOLIN: Planning with Continuous Linear Numeric Change
ent temporal and metric conditions and effects (Eycrich. Mattmiillcr. & Roger, 2009; Coles. Fox. Long. & Smith. 2008a; Gcrcvini. Sactti, & Serina, 200Journal of Artificial Intelligence Research 44 (2012) 1-96Submitted 01/12: published 05/12Colin: Planning with Continuous Linear Numeric ChangeAmanda COLIN: Planning with Continuous Linear Numeric Change ts in the solution of extended planning problems, including planning under uncertainty (Palacios & Gcffncr, 2009). planning with numbers and planning with time. However, the combination and integration of metric and temporal features, in which metric quantities change in lime-dependent ways, remains COLIN: Planning with Continuous Linear Numeric Change a challenge that has received relatively little attention.Interaction between time and numbers in planning problems can occur in many ways. In the siCOLIN: Planning with Continuous Linear Numeric Change
mplest case, using PDDL2.1 (Fox & Long. 2003), the numeric effects of actions arc only updated instantaneously, and only at the start or end points ofJournal of Artificial Intelligence Research 44 (2012) 1-96Submitted 01/12: published 05/12Colin: Planning with Continuous Linear Numeric ChangeAmanda COLIN: Planning with Continuous Linear Numeric Change hese restrictions. Time and numbers can interact in at least two more complex ways. First, actions can have variable, possibly constrained, durations and the (instantaneous) effects of these©2012 Al Access Foundation. All rights reserved.Colin: Planning with Continuous Changeas well as the machinery COLIN: Planning with Continuous Linear Numeric Change for confirming the temporal consistency of plans and the basis for the heuristic function. In Section 7 we describe systems in the literature that haCOLIN: Planning with Continuous Linear Numeric Change
ve addressed similar hybrid discrete-continuous planning problems to those that COLIN is designed to handle. Section 8 explains how state progression Journal of Artificial Intelligence Research 44 (2012) 1-96Submitted 01/12: published 05/12Colin: Planning with Continuous Linear Numeric ChangeAmanda COLIN: Planning with Continuous Linear Numeric Change consider several elements of COLIN that improve both efficiency and plan quality, without affecting the fundamental behaviour of the planner. Since time-dependent numeric change has been so little explored, there arc few benchmarks in existence that allow a full quantitative evaluation. We therefore COLIN: Planning with Continuous Linear Numeric Change present a collection of continuous domains that can be used for such analysis, and we show how COLIN fares on these. An appendix containing some explCOLIN: Planning with Continuous Linear Numeric Change
anations of technical detail and some detailed summaries of background work on which COLIN depends, ensures that the paper is complete and self-contaiJournal of Artificial Intelligence Research 44 (2012) 1-96Submitted 01/12: published 05/12Colin: Planning with Continuous Linear Numeric ChangeAmanda COLIN: Planning with Continuous Linear Numeric Change ent of discrete change, while COLIN can handle the full range of linear continuous numeric effects. The only metric functions of PDDL2.1 that are not in the repertoire of COLIN are scale-up and scale-down, which are non-linear updates, and the general form of plan metrics. Managing plan metrics defi COLIN: Planning with Continuous Linear Numeric Change ned in terms of domain variables remains a challenge for planning that has not yet [seen fully confronted by any contemporary planner. Colin does handCOLIN: Planning with Continuous Linear Numeric Change
le a restricted form of quality metric, which exploits an instrumented variable called total-cost. This allows COLIN to minimise the overall cost of tJournal of Artificial Intelligence Research 44 (2012) 1-96Submitted 01/12: published 05/12Colin: Planning with Continuous Linear Numeric ChangeAmanda COLIN: Planning with Continuous Linear Numeric Change itial Literals, an important feature that was introduced in PDDL2.2COLIN: Planning with Continuous Linear Numeric Change
in which it is applied. More general forms of conditional effect cannot be handled.With this collection of features. COLIN is able to fully manage botJournal of Artificial Intelligence Research 44 (2012) 1-96Submitted 01/12: published 05/12Colin: Planning with Continuous Linear Numeric ChangeAmanda COLIN: Planning with Continuous Linear Numeric Change f continuous change brought about by exogenous processes and events. These are triggered by actions, but they model the independent continuous behaviour brought about by the world rather than by the planner's direct action. The key additional features of PDDL+ that support this are processes and eve COLIN: Planning with Continuous Linear Numeric Change nts. Colin does not handle these features but is restricted to the management of continuous change as expressed through the durative action device.ForCOLIN: Planning with Continuous Linear Numeric Change
detailed explanations of the syntaxes and semantics of PDDL2.1 and PDDL+, including the semantics on which implementations of state representation anJournal of Artificial Intelligence Research 44 (2012) 1-96Submitted 01/12: published 05/12Colin: Planning with Continuous Linear Numeric ChangeAmanda COLIN: Planning with Continuous Linear Numeric Change & LongLanguageLanguage FeatureCriki:y3ColinCommentSection|’|>|>|.2.INumeric conditions and effectsyesyesBasic treatment follows Metric FFAppendix Bpdoi.2.1Continuous numeric effectsnoyesMtxlificaliun to state representationSection 8Modification to heuristicSection 9PDDL2.IGeneral plan metricsnonoPDD COLIN: Planning with Continuous Linear Numeric Change L2.IUseoftotal costnoyesLimited formSection 10PDDL2.1Assign (to discrete variables)yesyesTreatment follows Mctric-FFI’OOI 2.1Scale up/down111»no1’0012COLIN: Planning with Continuous Linear Numeric Change
.1Hl111»yesAs continuous effectsI’OOI 2.1Duralive actionsyesyesIncludes required concurrencySection 6 andAppendix c.PDDL2.1Duration inequalitieslimiteJournal of Artificial Intelligence Research 44 (2012) 1-96Submitted 01/12: published 05/12Colin: Planning with Continuous Linear Numeric ChangeAmanda Journal of Artificial Intelligence Research 44 (2012) 1-96Submitted 01/12: published 05/12Colin: Planning with Continuous Linear Numeric ChangeAmandaGọi ngay
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