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Entropy-Based Modeling and Simulation of Evolution in Biological Systems

  • Stanislaw Sieniutycz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4739)

Abstract

We report computer-aided modeling and simulation of evolution in biological systems with living organisms as effect of extremum properties of classical statistical entropy of Gibbs-Boltzmann type or its associates, e.g. Tsallis q-entropy. Evolution for animals with multiple organs is considered. A variational problem searches for the maximum entropy subject to the geometric constraint of constant thermodynamic distance in a non-Euclidean space of independent probabilities p i , plus possibly other constraints. Tensor dynamics is found. Some developmental processes progress in a relatively undisturbed way, whereas others may terminate rapidly due to inherent instabilities. For processes with variable number of states the extremum principle provides quantitative eveluation of biological development. The results show that a discrete gradient dynamics (governed by the entropy) can be predicted from variational principles for shortest paths and suitable transversality conditions.

Keywords

Maximum Entropy Generalize Entropy Classical Case Identical Organ Tensor Form 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Stanislaw Sieniutycz
    • 1
  1. 1.Faculty of Chemical Engineering, Warsaw University of Technology, 00-645 Warsaw, 1 Warynskiego StreetPoland

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