<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</abstract>

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.

(<italic>μ</italic> +<italic>λ</italic>) Evolution Strategy with Socio-Cognitive Mutation

Southern University of Science and Technology

Journal of Automation, Mobile Robotics and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

( +) Evolution Strategy with Socio-Cognitive Mutation

Socio-cognitive computing is a paradigm developed for the last several years in our research group. It consists of introducing mechanisms inspired by...

(μ +λ) Evolution Strategy with Socio-Cognitive Mutation

Publié en ligne: 13 avr. 2024

Pages: 1 - 11

Reçu: 08 févr. 2023

Accepté: 17 juil. 2023

DOI: https://doi.org/10.14313/jamris/1-2024/1

Mots clés
metaheuristics, socio-cognitive computing, global optimization

© 2024 Aleksandra Urbanczyk et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

(μ +λ) Evolution Strategy with Socio-Cognitive Mutation

Publié en ligne: 13 avr. 2024

Pages: 1 - 11

Reçu: 08 févr. 2023

Accepté: 17 juil. 2023

DOI: https://doi.org/10.14313/jamris/1-2024/1

Mots clésmetaheuristics, socio-cognitive computing, global optimization

© 2024 Aleksandra Urbanczyk et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
metaheuristics, socio-cognitive computing, global optimization