Corpus ID: 14963629

Reasoning about Categories in Conceptual Spaces

@inproceedings{Grdenfors2001ReasoningAC,
  title={Reasoning about Categories in Conceptual Spaces},
  author={Peter G{\"a}rdenfors and Mary-Anne Williams},
  booktitle={IJCAI},
  year={2001}
}
Understanding the process of categorization is a primary research goal in artificial intelligence. The conceptual space framework provides a flexible approach to modeling context-sensitive categorization via a geometrical representation designed for modeling and managing concepts. In this paper we show how algorithms developed in computational geometry, and the Region Connection Calculus can be used to model important aspects of categorization in conceptual spaces. In particular, we demonstrate… Expand
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104 Citations
Highly Influential Citations
9
Background Citations
43
Methods Citations
9

104 Citations

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Citation Type

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  • Computer Science, Mathematics
  • ArXiv
  • 2021
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The category of log-concave probabilistic channels between convex spaces is defined, which allows one to model fuzzy reasoning with noisy inputs, and provides a novel example of a Markov category. Expand
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This paper argues that most of the lexical relations that the authors need for plausible reasoning can be identified with qualitative spatial relations in semantic spaces, i.e. highdimensional Euclidean spaces in which words are represented as geometric objects. Expand
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  • Computer Science
  • 6th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007)
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Experimental results demonstrates conceptual spaces are superior to mere multidimensional feature spaces in concept learning and confirm the virtue of conceptual spaces. Expand
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