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Profiling Answer Set Programming: The Visualization Component of the noMoRe System

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Logics in Artificial Intelligence (JELIA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3229))

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Abstract

Standard debugging techniques, like sequential tracing, fail in answer set programming due to its purely declarative approach. We address this problem by means of the graph-oriented computational model underlying the noMoRe system. Although this is no generic solution, it offers a way to make the computation of answer sets transparent within the noMoRe framwork. Apart from the visualization of answer sets in terms of their generating rules, the computation can be animated in different ways.

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References

  1. Anger, C., Konczak, K., Linke, T.: NoMoRe: Non-monotonic reasoning with logic programs. In: Flesca, S., Greco, S., Leone, N., Ianni, G. (eds.) JELIA 2002. LNCS (LNAI), vol. 2424, p. 521. Springer, Heidelberg (2002)

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  2. Linke, T.: Graph theoretical characterization and computation of answer sets. In: Nebel, B. (ed.) Proceedings of the International Joint Conference on Artificial Intelligence, pp. 641–645. Morgan Kaufmann Publishers, San Francisco (2001)

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  3. Werner, M.: davinci v2.1.x online documentation (1998)

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© 2004 Springer-Verlag Berlin Heidelberg

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Bösel, A., Linke, T., Schaub, T. (2004). Profiling Answer Set Programming: The Visualization Component of the noMoRe System. In: Alferes, J.J., Leite, J. (eds) Logics in Artificial Intelligence. JELIA 2004. Lecture Notes in Computer Science(), vol 3229. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30227-8_61

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  • DOI: https://doi.org/10.1007/978-3-540-30227-8_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23242-1

  • Online ISBN: 978-3-540-30227-8

  • eBook Packages: Springer Book Archive

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