Heuristics, adapted from the work of Boyer and Moore, have been implemented as Prolog programs, called tactics, and used to guide an inductive proof checker, Oyster. Oyster reasons backwards from the theorem to be proved using a sequent calculus notation, which includes rules of inference for mathematical induction. The take out and unfold tactics then rewrite the base and step case, respectively, using the base and step equations of the recursive definition of . The two applications of take out rewrite the base case to an equation between two identical expressions, which the simplif y tactic reduces to true.
Harmelen, F. | Bundy, A.
We argue that explanation-based generalisation as recently proposed in the machine learning literature is essentially equivalent to partial evaluation, a well-known technique in the functional and logic programming literature. We show this equivalence by analysing the definitions and underlying algorithms of both techniques, and by giving a PROLOG program which can be interpreted as doing either explanation-based generalisation or partial evaluation.
Citation for published version: Bundy, A, Byrd, L, Luger, G, Mellish, C & Palmer, M 1979, 'Solving Mechanics Problems Using Meta-Level Inference'. in Proceedings of the 6th international joint conference on Artificial Intelligence - IJCAI '79. Link: Link to publication record in Edinburgh Research Explorer Document Version: Peer reviewed version Published In: Proceedings of the 6th international joint conference on Artificial Intelligence - IJCAI '79 General rights