A complexity-based approach in thermodynamic simulation of unstable evolutions in biosystems
Evolution of animals with multiple organs is considered. 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. 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 pi, plus possibly other constraints. Tensor form of dynamics is obtained. Some developmental processes progress in a relatively undisturbed way, whereas others may terminate rapidly due to inherent instabilities. 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.
evolution entropy gradient dynamics