Anna V Kononova
Anna V Kononova
LIACS, Leiden University
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Cited by
Deep multiagent reinforcement learning: Challenges and directions
A Wong, T Bäck, AV Kononova, A Plaat
Artificial Intelligence Review 56 (6), 5023-5056, 2023
Infeasibility and structural bias in differential evolution
F Caraffini, AV Kononova, D Corne
Information Sciences 496, 161-179, 2019
Structural bias in population-based algorithms
AV Kononova, DW Corne, P De Wilde, V Shneer, F Caraffini
Information Sciences 298, 468-490, 2015
Differential evolution outside the box
AV Kononova, F Caraffini, T Bäck
Information Sciences 581, 587-604, 2021
Structural bias in differential evolution: A preliminary study
F Caraffini, AV Kononova
AIP Conference Proceedings 2070 (1), 2019
Simple scheduled memetic algorithm for inverse problems in higher dimensions: Application to chemical kinetics
AV Kononova, DB Ingham, M Pourkashanian
2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on …, 2008
Fitness diversity based adaptive memetic algorithm for solving inverse problems of chemical kinetics
AV Kononova, KJ Hughes, M Pourkashanian, DB Ingham
2007 IEEE Congress on Evolutionary Computation, 2366-2373, 2007
Prudent-daring vs tolerant survivor selection schemes in control design of electric drives
F Neri, GL Cascella, N Salvatore, AV Kononova, G Acciani
Applications of Evolutionary Computing: EvoWorkshops 2006: EvoBIO, EvoCOMNET …, 2006
Bias: A toolbox for benchmarking structural bias in the continuous domain
D Vermetten, B van Stein, F Caraffini, LL Minku, AV Kononova
IEEE Transactions on Evolutionary Computation 26 (6), 1380-1393, 2022
Distinguishing normal, neuropathic and myopathic EMG with an automated machine learning approach
MR Tannemaat, M Kefalas, VJ Geraedts, L Remijn-Nelissen, ...
Clinical Neurophysiology 146, 49-54, 2023
Differential evolution with scale factor local search for large scale problems
A Caponio, AV Kononova, F Neri
Computational intelligence in expensive optimization problems, 297-323, 2010
Can compact optimisation algorithms be structurally biased?
AV Kononova, F Caraffini, H Wang, T Bäck
International Conference on Parallel Problem Solving from Nature, 229-242, 2020
Evolutionary algorithms for parameter optimization—thirty years later
THW Bäck, AV Kononova, B van Stein, H Wang, KA Antonov, ...
Evolutionary Computation 31 (2), 81-122, 2023
BBOB instance analysis: Landscape properties and algorithm performance across problem instances
FX Long, D Vermetten, B van Stein, AV Kononova
International Conference on the Applications of Evolutionary Computation …, 2023
Emergence of Structural Bias in Differential Evolution
B van Stein, F Caraffini, AV Kononova
The Genetic and Evolutionary Computation Conference (GECCO 2021), 1234-1242, 2021
Can single solution optimisation methods be structurally biased?
AV Kononova, F Caraffini, H Wang, T Bäck
2020 IEEE Congress on Evolutionary Computation (CEC), 1-9, 2020
Modular differential evolution
D Vermetten, F Caraffini, AV Kononova, T Bäck
Proceedings of the Genetic and Evolutionary Computation Conference, 864-872, 2023
Analysis of structural bias in differential evolution configurations
D Vermetten, B van Stein, AV Kononova, F Caraffini
Differential evolution: From theory to practice, 1-22, 2022
The Importance of Being Constrained: Dealing with Infeasible Solutions in Differential Evolution and Beyond
AV Kononova, D Vermetten, F Caraffini, MA Mitran, D Zaharie
Evolutionary Computation, 1-46, 2023
Is there anisotropy in structural bias?
D Vermetten, AV Kononova, F Caraffini, H Wang, T Bäck
The Genetic and Evolutionary Computation Conference (GECCO 2021), 1243-1250, 2021
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