Approximations of algorithmic and structural complexity validate cognitive-behavioral experimental results

Being able to objectively characterize the intrinsic complexity of behavioral patterns resulting from human or animal decisions is fundamental for deconvolving cognition and designing autonomous artificial intelligence systems. Yet complexity is difficult in practice, particularly when strings are s...

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Bibliographic Details
Main Authors: Hector Zenil, James A. R. Marshall, Jesper Tegnér
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-01-01
Series:Frontiers in Computational Neuroscience
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fncom.2022.956074/full