Some recent advances in reasoning based on analogical proportions

TL;DR

This paper explores recent improvements in reasoning using analogical proportions, focusing on enhancing inference accuracy, computational efficiency, and their potential for explanation, while revealing connections to multi-valued dependencies.

Contribution

It introduces novel methods to improve analogical inference accuracy and efficiency, and uncovers new links between analogical proportions and multi-valued dependencies.

Findings

Enhanced methods for analogical inference accuracy

Reduced computational costs in analogical reasoning

Identified relationships between analogical proportions and multi-valued dependencies

Abstract

Analogical proportions compare pairs of items (a, b) and (c, d) in terms of their differences and similarities. They play a key role in the formalization of analogical inference. The paper first discusses how to improve analogical inference in terms of accuracy and in terms of computational cost. Then it indicates the potential of analogical proportions for explanation. Finally, it highlights the close relationship between analogical proportions and multi-valued dependencies, which reveals an unsuspected aspect of the former.