ARVis: Visualizing Relations between Answer Sets

  • Thomas Ambroz
  • Günther Charwat
  • Andreas Jusits
  • Johannes Peter Wallner
  • Stefan Woltran
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8148)


Answer set programming (ASP) is nowadays one of the most popular modeling languages in the areas of Knowledge Representation and Artificial Intelligence. Hereby one represents the problem at hand in such a way that each model of the ASP program corresponds to one solution of the original problem. In recent years, several tools which support the user in developing ASP applications have been introduced. However, explicit treatment of one of the main aspects of ASP, multiple solutions, has received less attention within these tools. In this work, we present a novel system to visualize relations between answer sets of a given program. The core idea of the system is that the user specifies the concept of a relation by an ASP program itself. This yields a highly flexible system that suggests potential applications beyond development environments, e.g., applications in the field of abduction, which we will discuss in a case study.


Answer set programming Systems Abduction 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Brewka, G., Eiter, T., Truszczyński, M.: Answer set programming at a glance. Commun. ACM 54(12), 92–103 (2011)CrossRefGoogle Scholar
  2. 2.
    Charwat, G., Wallner, J.P., Woltran, S.: Utilizing ASP for generating and visualizing argumentation frameworks. In: ASPOCP 2012, pp. 51–65 (2012)Google Scholar
  3. 3.
    Cliffe, O., De Vos, M., Brain, M., Padget, J.: ASPVIZ: Declarative visualisation and animation using answer set programming. In: Garcia de la Banda, M., Pontelli, E. (eds.) ICLP 2008. LNCS, vol. 5366, pp. 724–728. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  4. 4.
    Eiter, T., Gottlob, G.: The complexity of logic-based abduction. J. ACM 42(1), 3–42 (1995)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Febbraro, O., Reale, K., Ricca, F.: ASPIDE: Integrated development environment for answer set programming. In: Delgrande, J.P., Faber, W. (eds.) LPNMR 2011. LNCS, vol. 6645, pp. 317–330. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  6. 6.
    Fruchterman, T.M.J., Reingold, E.M.: Graph drawing by force-directed placement. Softw., Pract. Exper. 21(11), 1129–1164 (1991)CrossRefGoogle Scholar
  7. 7.
    Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T., Schneider, M.: Potassco: The Potsdam answer set solving collection. AI Commun. 24(2), 105–124 (2011)MathSciNetGoogle Scholar
  8. 8.
    Hendler, J.A., Tate, A., Drummond, M.: AI planning: Systems and techniques. AI Magazine 11(2), 61–77 (1990)Google Scholar
  9. 9.
    Kamada, T., Kawai, S.: An algorithm for drawing general undirected graphs. Inf. Process. Lett. 31(1), 7–15 (1989)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Katsuno, H., Mendelzon, A.O.: Propositional knowledge base revision and minimal change. Artif. Intell. 52(3), 263–294 (1991)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Kloimüllner, C., Oetsch, J., Pührer, J., Tompits, H.: Kara: A system for visualising and visual editing of interpretations for answer-set programs. In: WLP 2011 (2011)Google Scholar
  12. 12.
    Leone, N., Pfeifer, G., Faber, W., Eiter, T., Gottlob, G., Perri, S., Scarcello, F.: The DLV system for knowledge representation and reasoning. ACM Trans. Comput. Log. 7(3), 499–562 (2006)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Oetsch, J., Pührer, J., Tompits, H.: The SeaLion has landed: An IDE for answer-set programming – Preliminary report. In: WLP 2011 (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Thomas Ambroz
    • 1
  • Günther Charwat
    • 1
  • Andreas Jusits
    • 1
  • Johannes Peter Wallner
    • 1
  • Stefan Woltran
    • 1
  1. 1.Institute of Information SystemsVienna University of TechnologyAustria

Personalised recommendations