Concepts from time series

Michael T. Rosenstein, Paul R. Cohen

Research output: Contribution to conferencePaperpeer-review

18 Scopus citations

Abstract

This paper describes a way of extracting concepts from streams of sensor readings. In particular, we demonstrate the value of attractor reconstruction techniques for transforming time series into clusters of points. These clusters, in turn, represent perceptual categories with predictive value to the agent/environment system. We also discuss the relationship between categories and concepts, with particular emphasis on class membership and predictive inference.

Original languageEnglish (US)
Pages739-745
Number of pages7
StatePublished - Jan 1 1998
EventProceedings of the 1998 15th National Conference on Artificial Intelligence, AAAI - Madison, WI, USA
Duration: Jul 26 1998Jul 30 1998

Other

OtherProceedings of the 1998 15th National Conference on Artificial Intelligence, AAAI
CityMadison, WI, USA
Period7/26/987/30/98

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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