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Publication search results
found 16 matches
- 2023
- Maxime Allard, Simón C. Smith, Konstantinos I. Chatzilygeroudis, Bryan Lim, Antoine Cully:
Online Damage Recovery for Physical Robots with Hierarchical Quality-Diversity. ACM Trans. Evol. Learn. Optim. 3(2): 6:1-6:23 (2023) - James R. Bradley, A. Paul Blossom:
The Generation of Visually Credible Adversarial Examples with Genetic Algorithms. ACM Trans. Evol. Learn. Optim. 3(1): 2:1-2:44 (2023) - Josu Ceberio, Valentino Santucci:
Model-based Gradient Search for Permutation Problems. ACM Trans. Evol. Learn. Optim. 3(4): 15:1-15:35 (2023) - Jonathan E. Fieldsend, Markus Wagner:
Editorial to the "Best of GECCO 2022" Special Issue: Part I. ACM Trans. Evol. Learn. Optim. 3(2): 4:1-4:2 (2023) - Manon Flageat, Félix Chalumeau, Antoine Cully:
Empirical analysis of PGA-MAP-Elites for Neuroevolution in Uncertain Domains. ACM Trans. Evol. Learn. Optim. 3(1): 1:1-1:32 (2023) - Fabrício Olivetti de França:
Transformation-Interaction-Rational Representation for Symbolic Regression: A Detailed Analysis of SRBench Results. ACM Trans. Evol. Learn. Optim. 3(2): 7:1-7:19 (2023) - Tobias Friedrich, Timo Kötzing, Aishwarya Radhakrishnan, Leon Schiller, Martin Schirneck, Georg Tennigkeit, Simon Wietheger:
Crossover for Cardinality Constrained Optimization. ACM Trans. Evol. Learn. Optim. 3(2): 5:1-5:32 (2023) - Adam Gaier, Giuseppe Paolo, Antoine Cully:
Editorial to the "Evolutionary Reinforcement Learning" Special Issue. ACM Trans. Evol. Learn. Optim. 3(3): 9:1-9:2 (2023) - Florian Karl, Tobias Pielok, Julia Moosbauer, Florian Pfisterer, Stefan Coors, Martin Binder, Lennart Schneider, Janek Thomas, Jakob Richter, Michel Lang, Eduardo C. Garrido-Merchán, Jürgen Branke, Bernd Bischl:
Multi-Objective Hyperparameter Optimization in Machine Learning - An Overview. ACM Trans. Evol. Learn. Optim. 3(4): 16:1-16:50 (2023) - Atsuhiro Miyagi, Yoshiki Miyauchi, Atsuo Maki, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Covariance Matrix Adaptation Evolutionary Strategy with Worst-Case Ranking Approximation for Min-Max Optimization and Its Application to Berthing Control Tasks. ACM Trans. Evol. Learn. Optim. 3(2): 8:1-8:32 (2023) - Federico Pigozzi, Eric Medvet, Alberto Bartoli, Marco Rochelli:
Factors Impacting Diversity and Effectiveness of Evolved Modular Robots. ACM Trans. Evol. Learn. Optim. 3(1): 3:1-3:33 (2023) - Joseph Renzullo, Westley Weimer, Stephanie Forrest:
Evolving Software: Combining Online Learning with Mutation-Based Stochastic Search. ACM Trans. Evol. Learn. Optim. 3(4): 13:1-13:32 (2023) - Olivier Sigaud:
Combining Evolution and Deep Reinforcement Learning for Policy Search: A Survey. ACM Trans. Evol. Learn. Optim. 3(3): 10:1-10:20 (2023) - Ashutosh Timilsina, Simone Silvestri:
P2P Energy Trading through Prospect Theory, Differential Evolution, and Reinforcement Learning. ACM Trans. Evol. Learn. Optim. 3(3): 11:1-11:22 (2023) - Paul-Antoine Le Tolguenec, Emmanuel Rachelson, Yann Besse, Dennis G. Wilson:
Curiosity Creates Diversity in Policy Search. ACM Trans. Evol. Learn. Optim. 3(3): 12:1-12:20 (2023) - Delaram Yazdani, Danial Yazdani, Donya Yazdani, Mohammad Nabi Omidvar, Amir H. Gandomi, Xin Yao:
A Species-based Particle Swarm Optimization with Adaptive Population Size and Deactivation of Species for Dynamic Optimization Problems. ACM Trans. Evol. Learn. Optim. 3(4): 14:1-14:25 (2023)
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