Compression and decompression in cognition

Michael O. Vertolli, Matthew A. Kelly, Jim Davies

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationArtificial General Intelligence - 7th International Conference, AGI 2014, Proceedings
PublisherSpringer Verlag
Pages262-265
Number of pages4
ISBN (Print)9783319092737
DOIs
StatePublished - Jan 1 2014
Event7th International Conference on Artificial General Intelligence, AGI 2014 - Quebec City, QC, Canada
Duration: Aug 1 2014Aug 4 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8598 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Artificial General Intelligence, AGI 2014
CountryCanada
CityQuebec City, QC
Period8/1/148/4/14

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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