Assembly Theory is an approximation to algorithmic complexity based on LZ compression that does not explain selection or evolution
arxiv(2024)
摘要
We demonstrate that Assembly Theory, pathway complexity, the assembly index,
and the assembly number are subsumed and constitute a weak version of
algorithmic (Kolmogorov-Solomonoff-Chaitin) complexity reliant on an
approximation method based upon statistical compression, their results obtained
due to the use of methods strictly equivalent to the LZ family of compression
algorithms used in compressing algorithms such as ZIP, GZIP, or JPEG. Such
popular algorithms have been shown to empirically reproduce the results of AT
that were reported before in successful application to separating organic from
non-organic molecules and in the context of the study of selection and
evolution. We prove the connections and full equivalence of Assembly Theory to
Shannon Entropy and statistical compression, and AT's disconnection as a
statistical approach from causality. We demonstrate that formulating a
traditional statistically compressed description of molecules, or the theory
underlying it, does not imply an explanation or quantification of biases in
generative (physical or biological) processes, including those brought about by
selection and evolution, when lacking in logical consistency and empirical
evidence. We argue that in their basic arguments, the authors of AT conflate
how objects may assemble with causal directionality, and conclude that Assembly
Theory does not explain selection or evolution beyond known and previously
established connections, some of which are reviewed.
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