Introducing the mathematical category of artificial perceptions

  • Z. Arzi-Gonczarowski
  • D. Lehmann


Perception is the recognition of elements and events in the environment, usually through integration of sensory impressions. It is considered here as a broad, high-level, concept (different from the sense in which computer vision/audio research takes the concept of perception). We propose and develop premises for a formal approach to a fundamental phenomenon in AI: the diversity of artificial perceptions. A mathematical substratum is proposed as a basis for a rigorous theory of artificial perceptions. A basic mathematical category is defined. Its objects are perceptions, consisting of world elements, connotations, and a three-valued (true, false, undefined) predicative correspondence between them. Morphisms describe paths between perceptions. This structure serves as a basis for a mathematical theory. This theory provides a way of extending and systematizing certain intuitive pre-theoretical conceptions about perception, about improving and/or completing an agent's perceptual grasp, about transition between various perceptions, etc. Some example applications of the theory are analyzed.


Choice Function Category Theory Unique Morphism Terminal Object Sensory Impression 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Kluwer Academic Publishers 1998

Authors and Affiliations

  • Z. Arzi-Gonczarowski
    • 1
  • D. Lehmann
    • 2
  1. 1.Typographics LtdJerusalemIsrael
  2. 2.Institute of Computer ScienceThe Hebrew University of JerusalemJerusalemIsrael

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