Answer set programming provides a powerful platform for model-based reasoning problems. The answer sets are solutions, but for many non-trivial problems post-processing is often necessary for human readability. In this paper we describe a method and a tool for visualising answer sets in which we exploit answer set programming itself to define how visualisations are constructed. An exciting potential application of our method is to assist in the debugging of answer set programs that, as a consequence of their declarative nature, are not amenable to traditional approaches: visual rendering of answer sets offers a way to help programmers spot false and missing solutions. © 2008 Springer Berlin Heidelberg.
CITATION STYLE
Cliffe, O., De Vos, M., Brain, M., & Padget, J. (2008). ASPVIZ: Declarative visualisation and animation using answer set programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5366 LNCS, pp. 724–728). https://doi.org/10.1007/978-3-540-89982-2_65
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