The Resolution Calculus

The History of the Book In August 1992 the author had the opportunity to give a course on resolution theorem proving at the Summer School for Logic, Language, and Information in Essex. The challenge of this course (a total of five two-hour lectures) con­ sisted in the selection of the topics to be presented. Clearly the first selection has already been made by calling the course "resolution theorem proving" instead of "automated deduction" . In the latter discipline a remarkable body of knowledge has been created during the last 35 years, which hardly can be presented exhaustively, deeply and uniformly at the same time. In this situ­ ation one has to make a choice between a survey and a detailed presentation with a more limited scope. The author decided for the second alternative, but does not suggest that the other is less valuable. Today resolution is only one among several calculi in computational logic and automated reasoning. How­ ever, this does not imply that resolution is no longer up to date or its potential exhausted. Indeed the loss of the "monopoly" is compensated by new appli­ cations and new points of view. It was the purpose of the course mentioned above to present such new developments of resolution theory. Thus besides the traditional topics of completeness of refinements and redundancy, aspects of termination (resolution decision procedures) and of complexity are treated on an equal basis.

This is a completely new presentation of resolution as a logical calculus and as a basis for computational algorithms and decision procedures.
The first part deals with the traditional topics (Herbrand's theorem, completeness of resolution, refinements and deletion) but with many new features and concepts like normalization of clauses, resolution operators, and search complexity.
Building on this foundation, the second part gives a systematic treatment of recent research topics. It is shown how resolution decision procedures can be applied to solve the decision problem for some important first-order classes. The complexity of resolution is analyzed in terms of Herbrand complexity, and new concepts like ground projection are used to classify the complexity of refinements. Finally, the method of functional extension is introduced; combined with resolution it gives a computational calculus which is stronger than most others.