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We show that the familiar explanation-based generalization (EBG) procedure is applicable to a large family of programming languages, including three families of importance to AI: logic programming (such as Pro-log); lambda calculus (such as LISP); and combinator languages (such as FP). The main application of this result is to extend the algorithm to(More)
A model is presented for the class of inductive inference problems that are solved by refinement algorithms-that is, algorithms that modify a hypothesis by making it more general or more specific in response to examples. The separate effects of the syntax (rule space) and semantics, and the relevant orderings on these, are precisely specified. Relations(More)