Learning and reasoning by analogy
Communications of the ACM
Machine Learning
Fuzzy Modelling of Case-Based Reasoning and Decision
ICCBR '97 Proceedings of the Second International Conference on Case-Based Reasoning Research and Development
Analogical Reasoning for Logic Programming
EWSL '91 Proceedings of the European Working Session on Machine Learning
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Learning by analogy: a classification rule for binary and nominal data
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Fuzzy set-based methods in instance-based reasoning
IEEE Transactions on Fuzzy Systems
Model adaptation in possibilistic instance-based reasoning
IEEE Transactions on Fuzzy Systems
Logical proportions: typology and roadmap
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
Interpolation and extrapolation in conceptual spaces: a case study in the music domain
RR'11 Proceedings of the 5th international conference on Web reasoning and rule systems
Evaluation of analogical proportions through Kolmogorov complexity
Knowledge-Based Systems
Analogy-Making for solving IQ tests: a logical view
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
Trying to understand how analogical classifiers work
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
Analogical proportions and multiple-valued logics
ECSQARU'13 Proceedings of the 12th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
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Analogical proportions are statements of the form "A is to B as C is to D" which play a key role in analogical reasoning. We propose a logical encoding of analogical proportions in a propositional setting, which is then extended to different fuzzy logics. Being in an analogical proportion is viewed as a quaternary connective relating four propositional variables. Interestingly enough, the fuzzy formalizations that are thus obtained parallel numerical models of analogical proportions. Potential applications to case-based reasoning and learning are outlined.