(196h) The Power of Unquantifiable Concepts: Evolutionary Fitness and Dynamics of Both Artificial and Biological Systems | AIChE

(196h) The Power of Unquantifiable Concepts: Evolutionary Fitness and Dynamics of Both Artificial and Biological Systems



Over one long professional lifetime the biological sciences have gone from a largely descriptive and empirical state to include the most exciting and sophisticated aspects of the traditional sciences, primarily because of their inherent complexity.  Recently developed areas of mathematics such as complexity theory have found some of their most impressive applications in modern biology, and important new concepts have arisen there. These advances have been expressed in new terms, and that to be examined here is evolutionary fitness, and more explicitly evolutionary fitness diagrams.

More generally the complexity of modern biology has emphasized the importance of heuristics always a key element of invention and other creative processes. To quote Henri Poincare’, a leading mathematician and exponent of logic:  “whereas it is by logic that we prove it is by intuition that we invent”. [S. J. Gould, Editor, 2001, “The Value of Science: Essential Writings of Henri Poincare’”, MIT Press] Even Albert Einstein used very simple diagrams in developing his major theories [Miller, A.I., “2000, “Insights of Genius”, Paperback Reprint Edition, MIT Press].       

Evolutionary fitness diagrams are based on the assumption that fitness for survival and reproduction can be expressed as a function of some number of parameters to be determined, of which only two can be expressed pictorially. They are often cited but never used to date except for very limited purposes:   the number of governing parameters can be extremely large and by no means all and their effects are known. 

However, it is our thesis here that the whole family of possible fitness diagrams may share some common properties and that examination of some simple special cases may provide useful suggestions for dealing with more complex situations. We therefore start the difficulty of climbing mountains, and we do find some common features that perhaps can be extended to more complex systems.

We hen do on, briefly, to other industrial systems, and we finish with speculations on major population and speciation dynamics.