IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v38y2019i2d10.1007_s10878-019-00389-y.html
   My bibliography  Save this article

A temporal logic programming approach to planning

Author

Listed:
  • Kai Yang

    (Institute of Computing Theory and Technology, and ISN Laboratory, Xidian University)

  • Cong Tian

    (Institute of Computing Theory and Technology, and ISN Laboratory, Xidian University)

  • Nan Zhang

    (Institute of Computing Theory and Technology, and ISN Laboratory, Xidian University)

  • Zhenhua Duan

    (Institute of Computing Theory and Technology, and ISN Laboratory, Xidian University)

  • Hongwei Du

    (Harbin Institute of Technology Shenzhen Graduate School)

Abstract

This paper presents an approach to performing artificial intelligence planning through temporal logic programming with Search Control Knowledge (SCK). First, the planning problem described with Planning Domain Description Language is modeled as a program m in Modeling, Simulation and Verification Language (MSVL). Second, the SCK is also specified with an MSVL program $$m'$$ m ′ . Third, using the basic operation “and” in MSVL, a new MSVL program “ $$m~and~m'$$ m a n d m ′ ” is obtained. Forth, with the compiler MC of MSVL, an executable binary code of program “ $$m~and~m'$$ m a n d m ′ ” is obtained. Finally, planning result can be obtained via executing the executable code. Experimental results on selected benchmark planning domains from the International Planning Competition 2014 show that our approach is more effective in practice. Furthermore, the obtained plans are verified with the toolkit MSV so that a plan can be confirmed whether it is a reliable one.

Suggested Citation

  • Kai Yang & Cong Tian & Nan Zhang & Zhenhua Duan & Hongwei Du, 2019. "A temporal logic programming approach to planning," Journal of Combinatorial Optimization, Springer, vol. 38(2), pages 402-420, August.
  • Handle: RePEc:spr:jcomop:v:38:y:2019:i:2:d:10.1007_s10878-019-00389-y
    DOI: 10.1007/s10878-019-00389-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-019-00389-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10878-019-00389-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Roman E. Shangin & Panos Pardalos, 2016. "Heuristics for the network design problem with connectivity requirements," Journal of Combinatorial Optimization, Springer, vol. 31(4), pages 1461-1478, May.
    2. Nan Zhang & Mengfei Yang & Bin Gu & Zhenhua Duan & Cong Tian, 2016. "Verifying safety critical task scheduling systems in PPTL axiom system," Journal of Combinatorial Optimization, Springer, vol. 31(2), pages 577-603, February.
    3. Rafael F. Santos & Alessandro Andrioni & Andre C. Drummond & Eduardo C. Xavier, 2017. "Multicolour paths in graphs: NP-hardness, algorithms, and applications on routing in WDM networks," Journal of Combinatorial Optimization, Springer, vol. 33(2), pages 742-778, February.
    4. Virginie Gabrel, 2006. "Strengthened 0-1 linear formulation for the daily satellite mission planning," Journal of Combinatorial Optimization, Springer, vol. 11(3), pages 341-346, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang Ye & Hu Xiaoxuan & Zhu Waiming & Jin Peng, 2018. "Solving the Observing and Downloading Integrated Scheduling Problem of Earth Observation Satellite with a Quantum Genetic Algorithm," Journal of Systems Science and Information, De Gruyter, vol. 6(5), pages 399-420, October.
    2. Chen, Xiaoyu & Reinelt, Gerhard & Dai, Guangming & Spitz, Andreas, 2019. "A mixed integer linear programming model for multi-satellite scheduling," European Journal of Operational Research, Elsevier, vol. 275(2), pages 694-707.
    3. Glaydston Mattos Ribeiro & Miguel Fragoso Constantino & Luiz Antonio Nogueira Lorena, 2010. "Strong formulation for the spot 5 daily photograph scheduling problem," Journal of Combinatorial Optimization, Springer, vol. 20(4), pages 385-398, November.
    4. Riccardo Dondi & Florian Sikora, 2018. "Finding disjoint paths on edge-colored graphs: more tractability results," Journal of Combinatorial Optimization, Springer, vol. 36(4), pages 1315-1332, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jcomop:v:38:y:2019:i:2:d:10.1007_s10878-019-00389-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.