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Opening the parallelogram: Considerations on non-Euclidean analogies
- Pierre-Alexandre Murena, Antoine Cornuéjols, Jean-Louis Dessalles
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- References
- International Conference on Case-Based Reasoning (ICCBR 2018), Stockholm, Suède, July 2018,
- Abstract
Analogical reasoning is a cognitively fundamental way of reasoning by comparing two pairs of elements. Several computational approaches are proposed to efficiently solve analogies: among them, a large number of practical methods rely on either a parallelogram representation of the analogy or, equivalently, a model of proportional analogy. In this paper, we propose to broaden this view by extending the parallelogram representation to differential manifolds, hence spaces where the notion of vectors does not exist. We show that, in this context, some classical properties of analogies do not hold any longer. We illustrate our considerations with two examples: analogies on a sphere and analogies on probability distribution manifold.
- Keywords
- machine learning, analogy, complexity
- Category
- Paper in proceedings
- Research Area(s)
- Computer Science/Machine Learning
Computer Science/Artificial Intelligence
- Identifier(s)
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Bibliographic key jld-18060701
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- Last update
- on january 28, 2019 by Jean-Louis Dessalles
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