A complexity based approach for solving Hofstadter's analogies

Publikationstyp
Conference Paper
Publikationsdatum
2017-06
Sprache
English
Author
Murena, Pierre Alexandre 
Dessalles, Jean Louis 
CornuĂ©jols, Antoine 
TORE-URI
http://hdl.handle.net/11420/15265
Enthalten in
CEUR workshop proceedings 
Volume
2028
Start Page
53
End Page
62
Citation
ICCBR Workshops on Computational Analogy and Case-Based Reasoning (CAW 2017)
Contribution to Conference
ICCBR Workshops on Computational Analogy and Case-Based Reasoning, CAW 2017 
Scopus ID
2-s2.0-85040350460
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.
Schlagworte
Analogy
Complexity
Relevance