Composability in Cognitive Hierarchies

  • David Rajaratnam
  • Bernhard Hengst
  • Maurice Pagnucco
  • Claude Sammut
  • Michael Thielscher
Conference paper

DOI: 10.1007/978-3-319-50127-7_4

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9992)
Cite this paper as:
Rajaratnam D., Hengst B., Pagnucco M., Sammut C., Thielscher M. (2016) Composability in Cognitive Hierarchies. In: Kang B., Bai Q. (eds) AI 2016: Advances in Artificial Intelligence. AI 2016. Lecture Notes in Computer Science, vol 9992. Springer, Cham

Abstract

This paper develops a theory of node composition in a formal framework for cognitive hierarchies. It builds on an existing model for the integration of symbolic and sub-symbolic representations in a robot architecture consisting of nodes in a hierarchy. A notion of behaviour equivalence between cognitive hierarchies is introduced and node composition operators that preserve this equivalence are defined. This work is significant in two respects. Firstly, it opens the way for a formal comparison between cognitive robotic systems. Secondly, composition, more precisely decomposition, has been shown to be important to many fields, and may therefore prove of practical benefit in the context of cognitive systems.

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • David Rajaratnam
    • 1
  • Bernhard Hengst
    • 1
  • Maurice Pagnucco
    • 1
  • Claude Sammut
    • 1
  • Michael Thielscher
    • 1
  1. 1.University of New South WalesSydneyAustralia

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