Abstract
Socio-cognitive computing is a paradigm developed for the last several years, it consists in introducing into metaheuristics mechanisms inspired by inter-individual learning and cognition. It was successfully applied in hybridizing ACO and PSO metaheuristics. In this paper we have followed our previous experiences in order to hybridize the acclaimed evolution strategies. The newly constructed hybrids were applied to popular benchmarks and compared with their referential versions.
The research presented in this paper has been financially supported by: Polish National Science Center Grant no. 2019/35/O/ST6/00570 “Socio-cognitive inspirations in classic metaheuristics.”; Polish Ministry of Science and Higher Education funds assigned to AGH University of Science and Technology.
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Urbańczyk, A., Nowak, B., Orzechowski, P., Moore, J.H., Kisiel-Dorohinicki, M., Byrski, A. (2021). Socio-cognitive Evolution Strategies. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12743. Springer, Cham. https://doi.org/10.1007/978-3-030-77964-1_26
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