The Road to a Measurable Quantitative Understanding of Self-Organization and Evolution

Abstract

This book has discussed some of the most important aspects in the current state of the sciences of complexity, self-organization, and evolution. A central theme in this field is the search for mechanisms that can explain the self-organization of complex systems. The quest for the main guiding principles for causal explanations can be viewed as a very timely and central aspect of this search. This book is devoted to such topics and is a necessary read for anyone working at the forefront of complexity, self-organization, and evolution. As an addition to the lines of reasoning in this book, we focus on a quantitative description of self-organization and evolution. To create a measure of a degree of organization, we have applied the Principle of Least Action from physics. Action for a trajectory is defined as the integral of the difference between kinetic and potential energy over time. This principle states that the equations of motion in nature are obeyed when action is minimized. In complex systems, there are constraints to motion that prevent the agents from moving along the paths of least action. Using free energy, those agents do work on the obstructive constraints to minimize them, in order to approach their natural state of motion given by the principle of least action. This is the process of self-organization. Therefore, the decrease in the amount of action for an agent along its path is a numerical measure for self-organization. This increase of action efficiency is a quantitative measure for the increase in organization and corresponding evolutionary level of the system. The least action state is the attractor for self-organization, and is achieved through feedback loops between the characteristics in complex systems. In our view the principle of least action applied to complex systems can introduce time dependence in nonequilibrium thermodynamics.