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.
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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. https://doi.org/10.1007/978-3-319-09274-4_30
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DOI: https://doi.org/10.1007/978-3-319-09274-4_30
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09273-7
Online ISBN: 978-3-319-09274-4
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