Compression and Decompression in Cognition

  • Michael O. Vertolli
  • Matthew A. Kelly
  • Jim Davies
Conference paper

DOI: 10.1007/978-3-319-09274-4_30

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8598)
Cite this paper as:
Vertolli M.O., Kelly M.A., Davies J. (2014) Compression and Decompression in Cognition. In: Goertzel B., Orseau L., Snaider J. (eds) Artificial General Intelligence. AGI 2014. Lecture Notes in Computer Science, vol 8598. Springer, Cham

Abstract

This paper proposes that decompression is an important and often overlooked component of cognition in all domains where compressive stimuli reduction is a requirement. We support this claim by comparing two compression representations, co-occurrence probabilities and holographic vectors, and two decompression procedures, top-n and Coherencer, on a context generation task from the visual imagination literature. We tentatively conclude that better decompression procedures increase optimality across compression types.

Keywords

decompression generative cognition imagination context coherence vector symbolic architectures cognitive modeling 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Michael O. Vertolli
    • 1
  • Matthew A. Kelly
    • 1
  • Jim Davies
    • 1
  1. 1.Institute of Cognitive ScienceCarleton UniversityOttawaCanada

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