Literature DB >> 21055440

Triadic conceptual structure of the maximum entropy approach to evolution.

Carsten Herrmann-Pillath1, Stanley N Salthe.   

Abstract

Many problems in evolutionary theory are cast in dyadic terms, such as the polar oppositions of organism and environment. We argue that a triadic conceptual structure offers an alternative perspective under which the information generating role of evolution as a physical process can be analyzed, and propose a new diagrammatic approach. Peirce's natural philosophy was deeply influenced by his reception of both Darwin's theory and thermodynamics. Thus, we elaborate on a new synthesis which puts together his theory of signs and modern Maximum Entropy approaches to evolution in a process discourse. Following recent contributions to the naturalization of Peircean semiosis, pointing towards 'physiosemiosis' or 'pansemiosis', we show that triadic structures involve the conjunction of three different kinds of causality, efficient, formal and final. In this, we accommodate the state-centered thermodynamic framework to a process approach. We apply this on Ulanowicz's analysis of autocatalytic cycles as primordial patterns of life. This paves the way for a semiotic view of thermodynamics which is built on the idea that Peircean interpretants are systems of physical inference devices evolving under natural selection. In this view, the principles of Maximum Entropy, Maximum Power, and Maximum Entropy Production work together to drive the emergence of information carrying structures, which at the same time maximize information capacity as well as the gradients of energy flows, such that ultimately, contrary to Schrödinger's seminal contribution, the evolutionary process is seen to be a physical expression of the Second Law.
Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Mesh:

Year:  2010        PMID: 21055440     DOI: 10.1016/j.biosystems.2010.10.014

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  2 in total

1.  Epidemic as a natural process.

Authors:  Mikko Koivu-Jolma; Arto Annila
Journal:  Math Biosci       Date:  2018-03-10       Impact factor: 2.144

2.  On the Use of Entropy Issues to Evaluate and Control the Transients in Some Epidemic Models.

Authors:  Manuel De la Sen; Raul Nistal; Asier Ibeas; Aitor J Garrido
Journal:  Entropy (Basel)       Date:  2020-05-09       Impact factor: 2.524

  2 in total

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