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Complexity issues for timeline-based planning over dense time under future and minimal semantics

Bozzelli L.
•
Montanari A.
•
Peron A.
2022
  • journal article

Periodico
THEORETICAL COMPUTER SCIENCE
Abstract
The problem of timeline-based planning (TP) over dense temporal domains is known to be undecidable in the general case. We first prove that the restriction to the future semantics does not suffice to recover decidability. Then, we introduce two semantic variants of TP, called strong minimal and weak minimal semantics, and show that they allow one to express meaningful properties. Both semantics are based on the minimality in the time distances of the existentially-quantified time events from the universally-quantified reference one, but the weak minimal variant distinguishes minimality in the past from minimality in the future. Surprisingly, we show that, despite the (apparently) small differences between the two semantics, the TP problem is still undecidable for the strong minimal one, while it is PSPACE-complete for the weak minimal one. Membership in PSPACE is determined by exploiting a strictly more expressive extension (ECA+) of the well-known robust class of Event-Clock Automata (ECA), that allows us to encode the weak minimal TP problem and to reduce it to non-emptiness of Timed Automata (TA). Finally, an extension of ECA+(ECA++) is considered, proving that its non-emptiness problem is undecidable. We believe that the two extensions of ECA (ECA+ and ECA++), introduced for technical reasons, are actually valuable per sé in the field of TA.1
DOI
10.1016/j.tcs.2021.12.004
WOS
WOS:000738342400006
Archivio
https://hdl.handle.net/11368/3032319
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85121424895
Diritti
open access
license:copyright editore
license:creative commons
license uri:iris.pri02
license uri:http://creativecommons.org/licenses/by-nc-nd/4.0/
FVG url
https://arts.units.it/request-item?handle=11368/3032319
Soggetti
  • Complexity

  • Dense time

  • Event-clock automata

  • Timed automata

  • Timeline-based planni...

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