---
title: "An Explanation-based Approach to Generalizing Number"
authors:
  - "Jude W. Shavlik"
  - "Gerald DeJong"
doi: ""
url: "https://ijcai.org/proceedings/1987/47"
pdf: "https://ijcai.org/proceedings/1987/0047.pdf"
venue: "Proceedings of the Tenth International Joint Conference on Artificial Intelligence"
year: 1987
pages: "236-237"
track: "Knowledge Acquisition"
keywords:
---

# An Explanation-based Approach to Generalizing Number

Jude W. Shavlik, Gerald DeJong

*Proceedings of the Tenth International Joint Conference on Artificial Intelligence*, pages 236-237.

## Abstract

An approach to generalizing number in explanation-based learning is presented. Generalizing number can involve generalizing such things as the number of entities involved in a concept or the number of times some action is performed. This issur has been largely ignored in previous explanation-based learning research. Instead. other research has focused on changing constants into variables and determining the genrral constraints on those variablrs . In the approach presented, gelleralization to N is triggrred by thr detection of inference rules of a specified syntactic form . When one is found, it is extended into the rule that results from an arbitrary number of repeated applications of the original rulr. If the preconditions of the extended rule are met, the rrsults of multiple applications of thr original rule are immediately drtrrmined . Thrre is no need to apply the underlying rule successively, each time checking if the preconditions for the next application are satisfied.