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. © 2014 Springer International Publishing.
CITATION STYLE
Vertolli, M. O., Kelly, M. A., & Davies, J. (2014). Compression and decompression in cognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8598 LNAI, pp. 262–265). Springer Verlag. https://doi.org/10.1007/978-3-319-09274-4_30
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