The Difficulties of Learning Logic Programs with Cut

TL;DR

This paper examines the challenges of learning logic programs that include the cut predicate, highlighting the limitations of existing methods and suggesting that current induction techniques may need restrictions for such programs.

Contribution

It introduces a novel approach to learning logic programs with cut by generating candidate bases and inserting cut, and analyzes the inherent difficulties involved.

Findings

Learning cut is inherently difficult due to procedural semantics.

Extensional evaluation methods are insufficient for programs with cut.

Current induction techniques should focus on purely declarative logic languages.

Abstract

As real logic programmers normally use cut (!), an effective learning procedure for logic programs should be able to deal with it. Because the cut predicate has only a procedural meaning, clauses containing cut cannot be learned using an extensional evaluation method, as is done in most learning systems. On the other hand, searching a space of possible programs (instead of a space of independent clauses) is unfeasible. An alternative solution is to generate first a candidate base program which covers the positive examples, and then make it consistent by inserting cut where appropriate. The problem of learning programs with cut has not been investigated before and this seems to be a natural and reasonable approach. We generalize this scheme and investigate the difficulties that arise. Some of the major shortcomings are actually caused, in general, by the need for intensional evaluation. As a conclusion, the analysis of this paper suggests, on precise and technical grounds, that learning cut is difficult, and current induction techniques should probably be restricted to purely declarative logic languages.