mpEAd: Multi-Population EA Diagrams
Sebastian Lenartowicz, Mark Wineberg

TL;DR
This paper introduces mpEAd, a formal notation and diagrammatic system for clearly representing complex multi-population evolutionary algorithms, enhancing understanding and discovery of new configurations.
Contribution
It provides a novel, consistent formalism and notation for visualizing multi-population evolutionary systems, addressing a gap in existing descriptive methods.
Findings
New configurations of co-evolutionary systems discovered visually.
Complex systems with many populations can be understood easily.
Formalism enhances clarity and facilitates system analysis.
Abstract
Multi-population evolutionary algorithms are, by nature, highly complex and difficult to describe. Even two populations working in concert (or opposition) present a myriad of potential configurations that are often difficult to relate using text alone. Little effort has been made, however, to depict these kinds of systems, relying solely on the simple structural connections (related using ad hoc diagrams) between populations and often leaving out crucial details. In this paper, we propose a notation and accompanying formalism for consistently and powerfully depicting these structures and the relationships within them in an intuitive and consistent way. Using our notation, we examine simple co-evolutionary systems and discover new configurations by the simple process of "drawing on a whiteboard". Finally, we demonstrate that even complex, highly-interconnected systems with large numbers…
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Taxonomy
TopicsEvolutionary Algorithms and Applications · Evolution and Genetic Dynamics · Metaheuristic Optimization Algorithms Research
