Stuart Kauffman

Entropy 2022, 24(10), 1383

Substantial grounds exist to doubt the universal validity of the Newtonian Paradigm that requires a pre-stated, fixed phase space. Therefore, the Second Law of Thermodynamics, stated only for fixed phase spaces, is also in doubt. The validity of the Newtonian Paradigm may stop at the onset of evolving life. Living cells and organisms are Kantian Wholes that achieve constraint closure, so do thermodynamic work to construct themselves. Evolution constructs an ever-expanding phase space. Thus, we can ask the free energy cost per added degree of freedom. That cost is roughly linear or sublinear in the mass constructed. However, the resulting expansion of the phase space is exponential or even hyperbolic. Thus, the evolving biosphere does thermodynamic work to construct itself into an ever-smaller sub-domain of its ever-expanding phase space at ever less free energy cost per added degree of freedom. The universe is not correspondingly disordered. Entropy, remarkably, really does decrease. A testable implication of this, termed here the Fourth Law of Thermodynamics, is that at constant energy input, the biosphere will construct itself into an ever more localized subregion of its ever-expanding phase space. This is confirmed. The energy input from the sun has been roughly constant for the 4 billion years since life started to evolve. The localization of our current biosphere in its protein phase space is at least 10–2540. The localization of our biosphere with respect to all possible molecules of CHNOPS comprised of up to 350,000 atoms is also extremely high. The universe has not been correspondingly disordered. Entropy has decreased. The universality of the Second Law fails.

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Abicumaran Uthamacumaran, Felipe S. Abraão, Narsis A. Kiani, Hector Zenil
A recently introduced approach termed “Assembly Theory”, featuring a computable index based on basic principles of statistical compression has been claimed to be a novel and superior approach to classifying and distinguishing living from non-living systems and the complexity of molecular biosignatures. Here, we demonstrate that the assembly pathway method underlying this index is a suboptimal restricted version of Huffman’s encoding (Fano-type), widely adopted in computer science in the 1950s, that is comparable (or inferior) to other popular statistical compression schemes. We show how simple modular instructions can mislead the assembly index, leading to failure to capture subtleties beyond trivial statistical properties that are pervasive in biological systems. We present cases whose low complexities can arbitrarily diverge from the random-like appearance to which the assembly pathway method would assign arbitrarily high statistical significance, and show that it fails in simple cases (synthetic or natural). Our theoretical and empirical results imply that the assembly index, whose computable nature we show is not an advantage, does not offer any substantial advantage over existing concepts and methods. Alternatives are discussed.

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Michele Braccini, Andrea Roli, Edoardo Barbieri, and Stuart A. Kauffman

Entropy 2022, 24(10), 1368

Systems poised at a dynamical critical regime, between order and disorder, have been shown capable of exhibiting complex dynamics that balance robustness to external perturbations and rich repertoires of responses to inputs. This property has been exploited in artificial network classifiers, and preliminary results have also been attained in the context of robots controlled by Boolean networks. In this work, we investigate the role of dynamical criticality in robots undergoing online adaptation, i.e., robots that adapt some of their internal parameters to improve a performance metric over time during their activity. We study the behavior of robots controlled by random Boolean networks, which are either adapted in their coupling with robot sensors and actuators or in their structure or both. We observe that robots controlled by critical random Boolean networks have higher average and maximum performance than that of robots controlled by ordered and disordered nets. Notably, in general, adaptation by change of couplings produces robots with slightly higher performance than those adapted by changing their structure. Moreover, we observe that when adapted in their structure, ordered networks tend to move to the critical dynamical regime. These results provide further support to the conjecture that critical regimes favor adaptation and indicate the advantage of calibrating robot control systems at dynamical critical states.

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