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To prove really difficult theorems, resolution principle programs need to make better inferences and to make them faster. An approach is presented for taking advantage of the structure of some special theories. These are theories with simplifiers, commutativity, and associativity, which are valuable concepts to build in, since they so frequently occur in(More)
The object of consequence-finding is to deduce logical consequences from a set of axioms. The theory of J.R. Slagle's semantic resolution principle , an inference rule for first-order predicate calculus, is extended to consequence-finding. Given an interpretation I, it is proved that any prime (non-trivial) consequence, which is false in I, can be derived(More)
We computer scientists face at least two problems in promoting the use of computerized data-base systems: 1) some important data might be missing; 2) there might be errors in the data. Both of these problems can be quite serious. If they cannot be solved, it will be quite hard to convince potential users that computerized information systems are useful.
A large high-speed general-purpose digital computer (IBM 7090) was Programmed to solve elementary symbolic integration problems at approximately the level of a good college freshman. The program is called SAINT, an acronym for "Symbolic Automatic INTegrator." The SAINT program is written in LISP (McCarthy, 1960), and most of the work reported here Js the(More)
We describe an expert system for resource allocation in a particular military domain. The system incorporates variants of several important techniques of artificial intelligence and makes the first use of the Merit system for question selection. This technique enables the system to direct the acquisition of information by finding questions with a high ratio(More)