---
title: "A Computational Model of Analogical Problem Solving"
authors:
  - "Jaime G. Carbonell"
doi: ""
url: "https://ijcai.org/proceedings/1981/31"
pdf: "https://ijcai.org/proceedings/1981/0031.pdf"
venue: "Proceedings of the Seventh International Joint Conference on Artificial Intelligence"
year: 1981
pages: "147-151"
track: "Learning"
keywords:
---

# A Computational Model of Analogical Problem Solving

Jaime G. Carbonell

*Proceedings of the Seventh International Joint Conference on Artificial Intelligence*, pages 147-151.

## Abstract

This paper outlines a theory of analogical reasoning based on a process-model of problem solving by analogy and the hypothesis that problem solving and learning are inalienable, concurrent processes in the human cognitive system . The analogical problem solver exploits prior experience in solving similar problems, and, in the process, augments a hierarchically-structured epsiodic long term memory . An analogical transformation process is developed based on a modified version of Means-Ends Analysis in order to map past solutions from similar problems into solutions satisfying the requirements of the new problem.