Exploration of Ontological Representations for Evolutionary Computation
Hugo Alcaraz‐Herrera, John Cartlidge · 2022 IEEE Congress on Evolutionary Computation (CEC) · 2022
This research explores the utility of ontological representations using object-oriented (OO) design principles, such that characteristics of the problem domain are directly mapped onto the representation of individuals. A comparison against more traditional representations is performed in two problem domains of differing complexity: (i) Tangram, a simple geometric puzzle; and (ii) EvoRecSys, an evolutionary recommender system for health and well-being advice. We show that OO representations aid research and development as naturally decoupled components can be more easily modified and extended, which can in turn lead to the discovery of better solutions.