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BUSTLE: A Versatile Tool for the Evolutionary Learning of STL Specifications from Data

Federico Pigozzi; Laura Nenzi; Eric Medvet

https://doi.org/10.1162/evco_a_00347

IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics

Jacob de Nobel; Furong Ye; Diederick Vermetten; Hao Wang; Carola Doerr; Thomas Bäck

https://doi.org/10.1162/evco_a_00342

A Tri-Objective Method for Bi-Objective Feature Selection in Classification

Ruwang Jiao; Bing Xue; Mengjie Zhang

https://doi.org/10.1162/evco_a_00339

Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems in Python

Raphael Patrick Prager; Heike Trautmann

https://doi.org/10.1162/evco_a_00341

Preliminary Analysis of Simple Novelty Search

R. Paul Wiegand

https://doi.org/10.1162/evco_a_00340

Discovering and Exploiting Sparse Rewards in a Learned Behavior Space

Giuseppe Paolo; Miranda Coninx; Alban Laflaquière; Stephane Doncieux

https://doi.org/10.1162/evco_a_00343

Evolutionary Sparsity Regularisation-based Feature Selection for Binary Classification

Bach Hoai Nguyen; Bing Xue; Mengjie Zhang

https://doi.org/10.1162/evco_a_00358

Landscape Analysis for Surrogate Models in the Evolutionary Black-Box Context

Zbyněk Pitra; Jan Koza; Jiří Tumpach; Martin Holeňa

https://doi.org/10.1162/evco_a_00357

Virtual Position Guided Strategy for Particle Swarm Optimization Algorithms on Multimodal Problems

Chao Li; Jun Sun; Li-Wei Li; Min Shan; Vasile Palade; Xiaojun Wu

https://doi.org/10.1162/evco_a_00352

Synthesising Diverse and Discriminatory Sets of Instances Using Novelty Search in Combinatorial Domains

Alejandro Marrero; Eduardo Segredo; Coromoto León; Emma Hart

https://doi.org/10.1162/evco_a_00350

OneMax Is Not the Easiest Function for Fitness Improvements

Marc Kaufmann; Maxime Larcher; Johannes Lengler; Xun Zou

https://doi.org/10.1162/evco_a_00348

Drift Analysis with Fitness Levels for Elitist Evolutionary Algorithms

Jun He; Yuren Zhou

https://doi.org/10.1162/evco_a_00349

A Layered Learning Approach to Scaling in Learning Classifier Systems for Boolean Problems

Isidro M. Alvarez; Trung B. Nguyen; Will N. Browne; Mengjie Zhang

https://doi.org/10.1162/evco_a_00351

Runtime Analysis of Single- and Multi-Objective Evolutionary Algorithms for Chance Constrained Optimization Problems with Normally Distributed Random Variables

Frank Neumann; Carsten Witt

https://doi.org/10.1162/evco_a_00355

Using Machine Learning Methods to Assess Module Performance Contribution in Modular Optimization Frameworks

Ana Kostovska; Diederick Vermetten; Peter Korošec; Sašo Džeroski; Carola Doerr; Tome Eftimov

https://doi.org/10.1162/evco_a_00356

Territorial Differential Meta-Evolution: An Algorithm for Seeking All the Desirable Optima of a Multivariable Function

Richard Wehr; Scott R. Saleska

https://doi.org/10.1162/evco_a_00337

Parameterless Gene-Pool Optimal Mixing Evolutionary Algorithms

Arkadiy Dushatskiy; Marco Virgolin; Anton Bouter; Dirk Thierens; Peter A. N. Bosman

https://doi.org/10.1162/evco_a_00338

Hyperparameter Control Using Fuzzy Logic: Evolving Policies for Adaptive Fuzzy Particle Swarm Optimization Algorithm

Nicolas Roy; Charlotte Beauthier; Alexandre Mayer

https://doi.org/10.1162/evco_a_00353

Large-Scale Multiobjective Evolutionary Algorithm Guided by Low-Dimensional Surrogates of Scalarization Functions

Haoran Gu; Handing Wang; Cheng He; Bo Yuan; Yaochu Jin

https://doi.org/10.1162/evco_a_00354

Neural Architecture Search Using Covariance Matrix Adaptation Evolution Strategy

Nilotpal Sinha; Kuan-Wen Chen

https://doi.org/10.1162/evco_a_00331

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