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Evolving look ahead controllers for energy optimal driving and path planning.

, and . INISTA, page 138-145. IEEE, (2014)

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Accelerating Evolutionary Design Exploration with Predictive and Generative Models. (Accélérer l'exploration de la conception par algorithme évolutionniste grâce à des modèles prédictifs et génératifs).. University of Lorraine, Nancy, France, (2020)COIL: Constrained optimization in learned latent space: learning representations for valid solutions., , , and . GECCO Companion, page 1870-1877. ACM, (2022)Data-efficient neuroevolution with kernel-based surrogate models., , and . GECCO, page 85-92. ACM, (2018)Multi-stage evolution of single- and multi-objective MCLP - Successive placement of charging stations., , , , and . Soft Comput., 21 (17): 4859-4872 (2017)Discovering representations for black-box optimization., , and . GECCO, page 103-111. ACM, (2020)Editorial to the "Evolutionary Reinforcement Learning" Special Issue., , and . ACM Trans. Evol. Learn. Optim., 3 (3): 9:1-9:2 (September 2023)Evolution of optimal control for energy-efficient transport., and . Intelligent Vehicles Symposium, page 1121-1126. IEEE, (2014)Are quality diversity algorithms better at generating stepping stones than objective-based search?, , and . GECCO (Companion), page 115-116. ACM, (2019)Feature Space Modeling Through Surrogate Illumination., , and . CoRR, (2017)Evolutionary Design via Indirect Encoding of Non-Uniform Rational Basis Splines.. GECCO (Companion), page 1197-1200. ACM, (2015)