We present a multiple predicate learner (MPL-Core) which efficiently induces some Horn clauses from example sets of multiple predicates and relative background knowledge. Core, a single predicate learning module, has a fast failure mechanism, and can select refinement operators based on the learning task. By means of GPC, an efficient pruning method, Core effectively prunes unpromising branches in a search tree, making the search space a rational volume. MPL-Core employs both the intensional and extensional learning style in the induction of target predicates. Furthermore, our system with the fast failure mechanism gives a distinct improvement over the existing multiple predicate learning systems in the computational complexity.
CITATION STYLE
Zhang, X., & Numao, M. (1996). Efficient multiple predicate learner based on fast failure mechanism. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1114, pp. 35–46). Springer Verlag. https://doi.org/10.1007/3-540-61532-6_4
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