Complexity for survival of livings

A connection between survivability of livings and complexity of their behavior is established. New physical paradigms—exchange of information via reflections, and chain of abstractions—explaining and describing progressive evolution of complexity in living (active) systems are introduced. A biological origin of these paradigms is associated with a recently discovered mirror neuron that is able to learn by imitation. As a result, an active element possesses the self–nonself images and interacts with them creating the world of mental dynamics. Three fundamental types of complexity of mental dynamics that contribute to survivability are identified. Mathematical model of the corresponding active systems is described by coupled motor-mental dynamics represented by Langevin and Fokker–Planck equations, respectively, while the progressive evolution of complexity is provided by nonlinear evolution of probability density. Application of the proposed formalism to modeling common-sense-based decision-making process is discussed.