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In his seminal work with NK algorithms, Kauffman noted that fitness outcomesfrom algorithms navigating an NK landscape show a sharp decline at highcomplexity arising from pervasive interdependence among problem dimensions.This phenomenon - where complexity effects dominate (Darwinian) adaptationefforts - is called complexity catastrophe. We present an algorithm -incremental change taking turns (ICTT) - that finds distant configurationshaving fitness superior to that reported in extant research, under highcomplexity. Thus, complexity catastrophe is not inevitable: a series ofincremental changes can lead to excellent outcomes.

Overcoming Complexity Catastrophe: An Algorithm for Beneficial Far-Reaching Adaptation under High Complexity