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(µ + λ) evolution strategy with socio-cognitive mutation

Urbanczyk Aleksandra, Kucaba Krzysztof, Wojtulewicz Mateusz, Kisiel-Dorohinicki Marek, Rutkowski Leszek, Duda Piotr, Kacprzyk Janusz, Yao Xin, Chong Siang Yew, Byrski Aleksander

Journal of Automation Mobile Robotics and Intelligent Systems

2024

Vol. 18, No. 1

1--11

Socio-cognitive computing is a paradigm developed for the last several years in our research group. It consists of introducing mechanisms inspired by inter-individual learning and cognition into metaheuristics. Different versions of the paradigm have been successfully applied in hybridizing Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Genetic Algorithms, Differential Evolution, and Evolutionary Multi-agent System (EMAS) metaheuristics. In this paper, we have followed our previous experiences in order to propose a novel mutation based on socio-cognitive mechanism and test it based on Evolution Strategy (ES). The newly constructed versions were applied to popular benchmarks and compared with their reference versions.