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