Fitness Optimization and Evolution of Permanent Replicator Systems

TL;DR

This paper explores how permanent replicator systems evolve their fitness landscapes over time, emphasizing the slow adaptation of system parameters compared to internal dynamics, grounded in Darwinian principles.

Contribution

It introduces a hypothesis that system parameter adaptation is slower than internal evolution, analyzing various adaptation scenarios within permanent replicator systems.

Findings

Fitness landscape evolution depends on slow parameter adaptation.

Steady-states follow Darwinian evolution principles.

Different adaptation cases are systematically considered.

Abstract

In this paper, we discuss the fitness landscape evolution of permanent replicator systems using a hypothesis that the specific time of evolutionary adaptation of the system parameters is much slower than the time of internal evolutionary dynamics. In other words, we suppose that the extreme principle of Darwinian evolution based the Fisher's fundamental theorem of natural selection is valid for the steady-states. Various cases of the evolutionary adaptation for permanent replicator system are considered.