Skip to main content

Advertisement

SpringerLink
  • Log in
Book cover

IFIP International Conference on Artificial Intelligence Applications and Innovations

AIAI 2015: Artificial Intelligence Applications and Innovations pp 130–150Cite as

  1. Home
  2. Artificial Intelligence Applications and Innovations
  3. Conference paper
Ordering Spatio-Temporal Sequences to Meet Transition Constraints: Complexity and Framework

Ordering Spatio-Temporal Sequences to Meet Transition Constraints: Complexity and Framework

  • Michael Sioutis19,
  • Jean-François Condotta19,
  • Yakoub Salhi19,
  • Bertrand Mazure19 &
  • …
  • David A. Randell20 
  • Conference paper
  • First Online: 15 November 2015
  • 1222 Accesses

  • 2 Citations

Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT,volume 458)

Abstract

Time and space are fundamental concepts of study in Artificial Intelligence and, in particular, Knowledge Representation. In this paper, we investigate the task of ordering a temporal sequence of qualitative spatial configurations to meet certain transition constraints. This ordering is constrained by the use of conceptual neighbourhood graphs defined on qualitative spatial constraint languages. In particular, we show that the problem of ordering a sequence of qualitative spatial configurations to meet such transition constraints is \(\mathcal{NP}\)-complete for the the well known languages of RCC-8, Interval Algebra, and Block Algebra. Based on this result, we also propose a framework where the temporal aspect of a sequence of qualitative spatial configurations is constrained by a Point Algebra network, and again show that the enhanced problem is in \(\mathcal{NP}\) when considering the aforementioned languages. Our results lie within the area of Graph Traversal and allow for many practical and diverse applications, such as identifying optimal routes in mobile robot navigation, modelling changes of topology in biological processes, and computing sequences of segmentation steps used in image processing algorithms.

Keywords

  • Base Relation
  • Hamiltonian Path
  • Transition Graph
  • Constraint Language
  • Mobile Robot Navigation

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This work was funded by Université d’Artois and region Nord-Pas-de-Calais.

Download conference paper PDF

References

  1. Allen, J.F.: Maintaining Knowledge about Temporal Intervals. Commun. ACM 26, 832–843 (1983)

    CrossRef  MATH  Google Scholar 

  2. van Beek, P.: Reasoning About Qualitative Temporal Information. Artif. Intell. 58, 297–326 (1992)

    CrossRef  MathSciNet  MATH  Google Scholar 

  3. van Beek, P., Cohen, R.: Exact and approximate reasoning about temporal relations. Computational Intelligence 6, 132–144 (1990)

    CrossRef  Google Scholar 

  4. Creignou, N., Khanna, S., Sudan, M.: Complexity Classifications of Boolean Constraint Satisfaction Problems. Monographs on Discrete Mathematics and Applications. Society for Industrial and Applied Mathematics (2001)

    Google Scholar 

  5. Cui, Z., Cohn, A.G., Randell, D.A.: Qualitative simulation based on a logical formalism of space and time. In: AAAI (1992)

    Google Scholar 

  6. Dylla, F., Mossakowski, T., Schneider, T., Wolter, D.: Algebraic properties of qualitative spatio-temporal calculi. In: Tenbrink, T., Stell, J., Galton, A., Wood, Z. (eds.) COSIT 2013. LNCS, vol. 8116, pp. 516–536. Springer, Heidelberg (2013)

    CrossRef  Google Scholar 

  7. Egenhofer, M.J.: The family of conceptual neighborhood graphs for region-region relations. In: Fabrikant, S.I., Reichenbacher, T., van Kreveld, M., Schlieder, C. (eds.) GIScience 2010. LNCS, vol. 6292, pp. 42–55. Springer, Heidelberg (2010)

    CrossRef  Google Scholar 

  8. Freksa, C.: Conceptual neighborhood and its role in temporal and spatial reasoning. In: Decision Support Systems and Qualitative Reasoning, pp. 181–187 (1991)

    Google Scholar 

  9. Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman & Co. (1979)

    Google Scholar 

  10. Guesgen, H.W.: Spatial Reasoning Based on Allen’s Temporal Logic. Tech. rep., International Computer Science Institute (1989)

    Google Scholar 

  11. Hazarika, S.: Qualitative Spatio-Temporal Representation and Reasoning: Trends and Future Directions. IGI Global (2012)

    Google Scholar 

  12. Krentel, M.W.: The Complexity of Optimization Problems. J. Comput. Syst. Sci. 36, 490–509 (1988)

    CrossRef  MathSciNet  MATH  Google Scholar 

  13. Randell, D.A., Cui, Z., Cohn, A.: A spatial logic based on regions and connection. In: KR (1992)

    Google Scholar 

  14. Randell, D.A., Landini, G., Galton, A.: Discrete Mereotopology for Spatial Reasoning in Automated Histological Image Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 35, 568–581 (2013)

    CrossRef  Google Scholar 

  15. Renz, J., Ligozat, G.: Weak composition for qualitative spatial and temporal reasoning. In: van Beek, P. (ed.) CP 2005. LNCS, vol. 3709, pp. 534–548. Springer, Heidelberg (2005)

    CrossRef  Google Scholar 

  16. Renz, J., Nebel, B.: Efficient Methods for Qualitative Spatial Reasoning. JAIR 15, 289–318 (2001)

    MathSciNet  MATH  Google Scholar 

  17. Santos, M.Y., Moreira, A.: Conceptual neighborhood graphs for topological spatial relations. In: WCE (2009)

    Google Scholar 

  18. Vilain, M., Kautz, H., van Beek, P.: Constraint propagation algorithms for temporal reasoning: A revised report. In: Readings in Qualitative Seasoning About Shysical Systems, pp. 373–381. Morgan Kaufmann Publishers Inc. (1990)

    Google Scholar 

  19. Westphal, M., Hué, J., Wölfl, S., Nebel, B.: Transition constraints: a study on the computational complexity of qualitative change. In: IJCAI (2013)

    Google Scholar 

  20. Wolter, F., Zakharyaschev, M.: Qualitative spatiotemporal representation and reasoning: A computational perspective. In: Exploring Artificial Intelligence in the New Millennium. Morgan Kaufmann Publishers Inc. (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. CRIL CNRS UMR 8188, Université d’Artois, Lens, France

    Michael Sioutis, Jean-François Condotta, Yakoub Salhi & Bertrand Mazure

  2. School of Dentistry, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK

    David A. Randell

Authors
  1. Michael Sioutis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jean-François Condotta
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yakoub Salhi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Bertrand Mazure
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. David A. Randell
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michael Sioutis .

Editor information

Editors and Affiliations

  1. Univ. de Pau et des Pays de l'Adour (UPPA), Anglet, France

    Richard Chbeir

  2. Aristotle University of Thessaloniki, Thessaloniki, Greece

    Yannis Manolopoulos

  3. University of Piraeus, Piraeus, Greece

    Ilias Maglogiannis

  4. University of Calgary, Calgary, Alberta, Canada

    Reda Alhajj

Rights and permissions

Reprints and Permissions

Copyright information

© 2015 IFIP International Federation for Information Processing

About this paper

Cite this paper

Sioutis, M., Condotta, JF., Salhi, Y., Mazure, B., Randell, D.A. (2015). Ordering Spatio-Temporal Sequences to Meet Transition Constraints: Complexity and Framework. In: Chbeir, R., Manolopoulos, Y., Maglogiannis, I., Alhajj, R. (eds) Artificial Intelligence Applications and Innovations. AIAI 2015. IFIP Advances in Information and Communication Technology, vol 458. Springer, Cham. https://doi.org/10.1007/978-3-319-23868-5_10

Download citation

  • .RIS
  • .ENW
  • .BIB
  • DOI: https://doi.org/10.1007/978-3-319-23868-5_10

  • Published: 15 November 2015

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23867-8

  • Online ISBN: 978-3-319-23868-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Share this paper

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Over 10 million scientific documents at your fingertips

Switch Edition
  • Academic Edition
  • Corporate Edition
  • Home
  • Impressum
  • Legal information
  • Privacy statement
  • California Privacy Statement
  • How we use cookies
  • Manage cookies/Do not sell my data
  • Accessibility
  • FAQ
  • Contact us
  • Affiliate program

Not logged in - 44.200.168.16

Not affiliated

Springer Nature

© 2023 Springer Nature Switzerland AG. Part of Springer Nature.