Nonlinear learning and learning advantages in evolutionary games

TL;DR

This paper investigates how nonlinear adaptation functions influence social competition and survival in evolutionary games, emphasizing the importance of initial incompetence levels and environmental fluctuations.

Contribution

It introduces the concept of nonlinear learning advantages and analyzes their impact on evolutionary stability and species survival under changing environments.

Findings

Nonlinear adaptation functions significantly alter competitive dynamics.

Initial incompetence levels are crucial for species survival.

Environmental fluctuations can lead to vulnerability of stable populations.

Abstract

The idea of incompetence as a learning or adaptation function was introduced in the context of evolutionary games as a fixed parameter. However, live organisms usually perform different nonlinear adaptation functions such as a power law or exponential fitness growth. Here, we examine how the functional form of the learning process may affect the social competition between different behavioral types. Further, we extend our results for the evolutionary games where fluctuations in the environment affect the behavioral adaptation of competing species and demonstrate importance of the starting level of incompetence for survival. Hence, we define a new concept of learning advantages that becomes crucial when environments are constantly changing and requiring rapid adaptation from species. This may lead to the evolutionarily weak phase when even evolutionary stable populations become vulnerable to invasions.