Abstract
A novel inductive logic programming system, called Classic'cl is presented. Classic'cl integrates several settings for learning, in particular learning from interpretations and learning from satisfiability. Within these settings, it addresses descriptive and probabilistic modeling tasks. As such, Classic'cl (C-armr, cLAudien, icl-S(S)at, ICI, and CLIpad) integrates several well-known inductive logic programming systems such as Claudien, Warmr (and its extension C-armr), ICL, ICL-SAT, and LLPAD. We report on the implementation, the integration issues as well as on some experiments that compare Classic'cl with some of its predecessors. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Stolle, C., Karwath, A., & De Raedt, L. (2005). Classic’cl: An integrated ILP system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3735 LNAI, pp. 354–362). https://doi.org/10.1007/11563983_31
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