| 2022 | EvoRobogami: co-designing with humans in evolutionary robotics experiments. | Zonghao Huang, Quinn Wu, David Howard, Cynthia R. Sung |
| 2022 | Graph-based linear genetic programming: a case study of dynamic scheduling. | Zhixing Huang, Yi Mei, Fangfang Zhang, Mengjie Zhang |
| 2022 | Assessing evolutionary terrain generation methods for curriculum reinforcement learning. | David Howard, Humphrey Munn, Davide Dolcetti, Josh Kannemeyer, Nicole L. Robinson |
| 2022 | Benchmarking an algorithm for expensive high-dimensional objectives on the bbob and bbob-largescale testbeds. | Zachary Hoffman, Steve Huntsman |
| 2022 | Reproducibility and baseline reporting for dynamic multi-objective benchmark problems. | Daniel Herring, Michael Kirley, Xin Yao |
| 2022 | Archivers for single- and multi-objective evolutionary optimization algorithms. | Carlos Hernndez, Oliver Schtze |
| 2022 | A bounded archive based for bi-objective problems based on distance and e-dominance to avoid cyclic behavior. | Carlos Hernndez, Oliver Schtze |
| 2022 | Measuring the ability of lexicase selection to find obscure pathways to optimality. | Jose Guadalupe Hernandez, Alexander Lalejini, Charles Ofria |
| 2022 | Phylogenetic diversity predicts future success in evolutionary computation. | Jose Guadalupe Hernandez, Alexander Lalejini, Emily L. Dolson |
| 2022 | Taylor genetic programming for symbolic regression. | Baihe He, Qiang Lu, Qingyun Yang, Jake Luo, Zhiguang Wang |
| 2022 | Lexicase selection. | Thomas Helmuth, William G. La Cava |
| 2022 | Benchmarking ϵMAg-ES and BP-ϵMAg-ES on the bbob-constrained testbed. | Michael Hellwig, Hans-Georg Beyer |
| 2022 | Separating rule discovery and global solution composition in a learning classifier system. | Michael Heider, Helena Stegherr, Jonathan Wurth, Roman Sraj, Jrg Hhner |
| 2022 | An overview of LCS research from 2021 to 2022. | Michael Heider, David Ptzel, Alexander R. M. Wagner |
| 2022 | Incorporating sub-programs as knowledge in program synthesis by PushGP and adaptive replacement mutation. | Yifan He, Claus Aranha, Tetsuya Sakurai |
| 2022 | Active learning improves performance on symbolic regression tasks in StackGP. | Nathan Haut, Wolfgang Banzhaf, Bill Punch |
| 2022 | Genetic improvement: taking real-world source code and improving it using computational search methods. | Smundur skar Haraldsson, Alexander E. I. Brownlee, John R. Woodward, Bradley Alexander, Emily Winter |
| 2022 | Addressing tactic volatility in self-adaptive systems using evolved recurrent neural networks and uncertainty reduction tactics. | Aizaz Ul Haq, Niranjana Deshpande, AbdElRahman ElSaid, Travis Desell, Daniel E. Krutz |
| 2022 | Benchmarking CMA-ES with margin on the bbob-mixint testbed. | Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa |
| 2022 | CMA-ES with margin: lower-bounding marginal probability for mixed-integer black-box optimization. | Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa |
| 2022 | Reduction of genetic drift in population-based incremental learning via entropy regularization. | Ryoki Hamano, Shinichi Shirakawa |
| 2022 | Comparing optimistic and pessimistic constraint evaluation in shape-constrained symbolic regression. | Christian Haider, Fabrcio Olivetti de Frana, Gabriel Kronberger, Bogdan Burlacu |
| 2022 | Multi-objective recommender system for corporate MOOC. | Mounir Hafsa, Pamela Wattebled, Julie Jacques, Laetitia Jourdan |
| 2022 | Improved data clustering using multi-trial vector-based differential evolution with gaussian crossover. | Parham Hadikhani, Daphne Teck Ching Lai, Wee-Hong Ong, Mohammad H. Nadimi-Shahraki |
| 2022 | PreDive: preserving diversity in test cases for evolving digital circuits using grammatical evolution. | Krishn Kumar Gupt, Meghana Kshirsagar, Lukas Rosenbauer, Joseph P. Sullivan, Douglas Mota Dias, Conor Ryan |