Exploring population geometry and multi-agent systems: a new approach to developing evolutionary techniques

Evolutionary algorithms require efficient recombination and selection mechanisms in order to produce high-quality solutions. In order to guide recombination a geometrical structure of the population is introduced. The aim of this paper is to explore connections between population geometry and individual interactions inducing autonomy, communication and reactivity. Each individual in the population acts as an autonomous agent with the goal of optimizing its fitness. In this process, each individual is able to communicate and select a mate for recombination. The introduced paradigm is illustrated by an evolutionary technique relying on a new population model and agent-based selection for recombination strategy. Search operators are asynchronously applied making the proposed approach more realistic. Numerical experiments indicate the potential of the proposed evolutionary agent-driven technique.