Recognizing unnecessary inference

Authors:
Dan Benanav
Affiliations:
Rensselaer Polytechnic Institute, Computer Science Department, Troy, NY
Venue:
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Year:
1989

Citing 6
Cited 0

The computer modelling of mathematical reasoning

The computer modelling of mathematical reasoning
Automated reasoning: 33 BASIC research problems

Automated reasoning: 33 BASIC research problems
Recognizing unnecessary inference

Recognizing unnecessary inference
A Machine-Oriented Logic Based on the Resolution Principle

Journal of the ACM (JACM)
Symbolic Logic and Mechanical Theorem Proving

Symbolic Logic and Mechanical Theorem Proving
Automated theorem proving: A logical basis (Fundamental studies in computer science)

Automated theorem proving: A logical basis (Fundamental studies in computer science)

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Abstract

Intelligent reasoners sometimes draw conclusions that lack new or relevant information. Similarly, automated reasoning systems can produce formulas that are not necessary for the problem at hand. We concentrate on the problem of unnecessary inference in the context of resolution based systems. In such systems several strategies have been developed that allow for the deletion of clauses without sacrificing completeness. Unfortunately these strategies fail to recognize other frequently generated unnecessary formulas. We will present a generalized subsumption theorem that can be used to recognize such formulas and to develop new deletion methods which retain completeness.