N IN AN ABSTRACTION SPACE: A Form of Constructive Induction George Drastal and Gabor Czako Siemens Research and Technology Laboratories 755 College Rd Princeton, NJ 08540 We report on a learning system MIRO which performs suconcept formation in an abstraction space. Given theory, the method constructs this abstraction space by deduction over instances, and then performs induction in it rather than the initial space defined by instances alone. It is also possible to regard MIRO as a variant of constructive induction. The Vapnik-Chervonenkis ggests that learning in an abstraction space can result in a substantial speedup, and we provide empirical studies which validate this proposition. We also show that in an abstraction space can reduce the number of false negative and false postive classifications because coincidental patterns are filtered by the deduction process. The method is able to extend an incomplete domain theory represented as at tribute-value pairs with a set of rules that ...