Measuring the Feasibility of Analogical Transfer using Complexity

Thumbnail Image

Access rights

openAccess
publishedVersion

URL

Journal Title

Journal ISSN

Volume Title

A4 Artikkeli konferenssijulkaisussa
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)

Authors

Date

2022

Department

Department of Computer Science

Major/Subject

Mcode

Degree programme

Language

en

Pages

13

Series

CEUR Workshop Proceedings, Volume 3174, pp. 62-74

Abstract

Analogies are 4-ary relations of the form “A is to B as C is to D". While focus has been mostly on how to solve an analogy, i.e. how to find correct values of D given A, B and C, less attention has been drawn on whether solving such an analogy was actually feasible. In this paper, we propose a quantification of the transferability of a source case (A and B) to solve a target problem C. This quantification is based on a complexity minimization principle which has been demonstrated to be efficient for solving analogies. We illustrate these notions on morphological analogies and show its connections with machine learning, and in particular with Unsupervised Domain Adaptation.

Description

Funding Information: The author wishes to thank the anonymous reviewers for their insightful comments and suggestions. Some of the presented ideas have been inspired by discussions with Antoine Cornuéjols, Jean-Louis Dessalles, Marie Al-Ghossein and Miguel Couceiro. This work was supported by the Academy of Finland Flagship programme: Finnish Center for Artificial Intelligence, FCAI. Publisher Copyright: © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Keywords

Analogical reasoning, Analogical transfer, Domain adaptation, Minimum Message Length

Other note

Citation

Murena, P A 2022, 'Measuring the Feasibility of Analogical Transfer using Complexity', CEUR Workshop Proceedings, vol. 3174, pp. 62-74.

Permanent link to this item

https://urn.fi/URN:NBN:fi:aalto-202209145560

Collections

[article-cris] Perustieteiden korkeakoulu / SCI