Erhard Glötzl

The general evolutionary theory can be seen as a comprehensive generalization and extension of Darwin's theory. The basic idea is to consider not only the evolution of genetic information - as Darwin did - but also the evolution of very general information. It shows that evolution is characterized by the fact that new types of information have developed in leaps and bounds, each with new storage technologies, new duplication technologies and new processing technologies. This unified concept of evolution makes it possible, among other things, to 1) achieve a unified view of biological and cultural evolution; 2) find a natural periodization of the evolution from the formation of the earth until today; and 3) understand the exponential acceleration of evolution through the emergence of targeted variation mechanisms.

The basic concern of the general theory of evolution is to understand the entire evolution from the origin of life to the biological, technological, social, and economic structures of the present from a unified point of view and structure. The general theory of evolution can be seen as a comprehensive generalization and extension of Darwin's theory of evolution. It goes far beyond conventional extensions of Darwinian theory, such as synthetic evolutionary theory or multistage selection or evo-devo or epigenetics. Essentially, it views evolution from the perspective of the evolution of information. It expands the Darwinian terms of "biological species," "genotype," "phenotype," "mutation," and "selection" and replaces them with much more general terms. These conceptual extensions make it possible to describe evolutionary developments in quite different areas from a unified point of view and within a unified time frame.The basic idea is to understand the evolution of everything as the emergence of new information types and new information technologies in the following sense:- A new type of information is associated with the emergence of a new storage technology- For each new type of information, 3 information technologies emerge one after the other:Storage technology, Duplication technology, processing technology.With this concept, the chronology of the entire evolution can be divided in a natural way into 7 ages with 3 sub-ages each, which correspond to the 7 information types with their corresponding 3 information technologies. Better and better information technologies are the basis for the fact that more and better targeted variation mechanisms could be formed. This explains the exponential increase in the speed of development and why development is probably heading for a singular point.The following topics represent a selection of new ideas presented in detail in the paper:- Evolutionary theory of information- Link between the evolutionary theory of information and the general theory of evolution.- Megatrends of evolution- Evolution of the driving forces- Targeted variation mechanisms as essential elements of evolution- Constraints as essential elements of evolution- The illusion of free will as an evolutionary trait of success- The documentation of debt relationships (especially in the form of money) as a catalyst for win-win and cooperation mechanisms- The difference between individual utility optimization and total utility maximization- From Artificial Intelligence 1.0 to Artificial Intelligence 2.0

This paper introduces a novel method to extend the Helmholtz Decomposition to n-dimensional sufficiently smooth and fast decaying vector fields. The rotation is described by a superposition of n(n-1)/2 rotations within the coordinate planes. The source potential and the rotation potential are obtained by convolving the source and rotation densities with the fundamental solutions of the Laplace equation. The rotation-free gradient of the source potential and the divergence-free rotation of the rotation potential sum to the original vector field. The approach relies on partial derivatives and Newton integrals and allows for a simple application of this standard method to high-dimensional vector fields, without using concepts from differential geometry and tensor calculus.

We present a differential-algebraic equation framework of constrained dynamics to implement monetary Stock-Flow Consistent (SFC) models. Agents exert forces on the variables according to their desire, for instance to gradually improve their utility. The parameter ‘economic power’ corresponds to their ability to assert their interest. In analogy to Lagrangian mechanics, system constraints from accounting identities generate additional constraint forces that lead to unintended dynamics. We exemplify the procedure using a simple SFC model and reveal its implicit assumptions about power relations and agents’ preferences.