Emergence of Adaptive Searching Rules from the Dynamics of a Simple Nonlinear System

Abstract

Various organisms share certain basic rules for a searching behavior. We hypothesize that these rules may emerge from basic properties of nonlinear systems as a whole, rather then being evolved from a scratch gradually. In order to support this hypothesis, we have developed a virtual agent that consists of three simple nonlinear oscillators. These oscillators are driven by an internal noise, which results in phase transitions in their activity. External stimuli modify the activity via sensors and food consumption. The interaction among the activity of oscillators and external influences give rise to an emergence of searching rules that are similar to those shared by various organisms, thus favoring this hypothesis. The hypothesis can be verified further by investigating various types of nonlinear systems in different environments.