A complexity based approach for solving Hofstadter's analogies
Publikationstyp
Conference Paper
Date Issued
2017-06
Sprache
English
Journal
Volume
2028
Start Page
53
End Page
62
Citation
Computational Analogy Workshop, (CAW 2017) and 25th International Conference on Case-Based Reasoning, (ICCBR 2017)
Scopus ID
Analogical reasoning is a central problem both for human cognition and for artificial learning. Many aspects of this problem remain unsolved, though, and analogical reasoning is still a difficult task for machines. In this paper, we consider the problem of analogical reasoning and assume that the relevance of a solution can be measured by the complexity of the analogy. This hypothesis is tested in a basic alphanumeric micro-world. In order to compute complexity, we present specifications for a prototype language used to describe analogies. A few elementary operators for this language are exposed, and their complexity is discussed both from a theoretical and practical point of view. We expose several alternative definitions of relevance in analogical reasoning and show how they are related to complexity.
Subjects
Analogy
Complexity
Relevance
DDC Class
600: Technology