---
title: "Combining Weak Learning Heuristics in General Problem Solvers"
authors:
  - "Thomas Leo McCluskey"
doi: ""
url: "https://ijcai.org/proceedings/1987/68"
pdf: "https://ijcai.org/proceedings/1987/0068.pdf"
venue: "Proceedings of the Tenth International Joint Conference on Artificial Intelligence"
year: 1987
pages: "331-332"
track: "Knowledge Acquisition"
keywords:
---

# Combining Weak Learning Heuristics in General Problem Solvers

Thomas Leo McCluskey

*Proceedings of the Tenth International Joint Conference on Artificial Intelligence*, pages 331-332.

## Abstract

This paper is concerned with state space problem solvers that achieve generality by learning strong heuristics through experience in a particular domain. We specifically consider two ways of learning by analysing past solutions that can improve future problem solving: creating macros and the chunks. A method of learning search heuristics is specified which is related to 'chunking' but which complements the use of macros within a goal directed system. An example of the creation and combined use of macros and chunks, taken from an implemented system, is described.