---
title: "Symbolic Revision of Theories with M-of-N Rules"
authors:
  - "Paul T. Baffes"
  - "Raymond J. Mooney"
doi: ""
url: "https://ijcai.org/proceedings/1993/157"
pdf: "https://ijcai.org/proceedings/1993/0157.pdf"
venue: "Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence"
year: 1993
pages: "1135-1141"
track: "Machine Learning"
keywords:
---

# Symbolic Revision of Theories with M-of-N Rules

Paul T. Baffes, Raymond J. Mooney

*Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence*, pages 1135-1141.

## Abstract

This paper presents a major rev1s1on of the EITHER propositional theory refinement system. Two issues are discussed. First, we show how run time efficiency can be greatly improved by changing from a exhaustive scheme for computing repairs to an iterative greedy method . Second, we show how to extend EITHER to refine M-of-N rules. The resulting algorithm, NEITHER (New EITHER), is more than an order of magnitude faster and produces significantly more accurate results with theories that fit the M-of-N format. To demonstrate the advantages of NEITHER, we present preliminary experimental results comparing it to EITHER and various other systems on refining the DNA promoter domain theory.