Stable Ilp : Exploring the Added Expressivity of Negation in the Background Knowledge
نویسنده
چکیده
We present stable ILP, a cross-disciplinary concept straddling machine learning and nonmonotonic reasoning. Stable models give meaning to logic programs containing negative assertions. In stable ILP, we employ stable models to represent the current state speciied by (possibly) negative EDB and IDB rules. The state then serves as the background knowledge for a top-down ILP learner. We present a framework and implementation (system INDED) of one realization of stable ILP.
منابع مشابه
Stable ILP : Exploring the Added Expressivity of
We present stable ILP, a cross-disciplinary concept straddling machine learning and nonmonotonic reasoning. Stable models give meaning to logic programs containing negative assertions. In stable ILP, we employ stable models to represent the current state speciied by (possibly) negative EDB and IDB rules. The state then serves as the background knowledge for a top-down ILP learner. We present a ...
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