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GECCO 2023: Lisbon, Portugal
- Sara Silva, Luís Paquete:
Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2023, Lisbon, Portugal, July 15-19, 2023. ACM 2023, ISBN 979-8-4007-0119-1
Keynote Talk
- Kenneth A. De Jong:
Evolutionary Computation Evolving. 1 - Carla Pedro Gomes:
AI for Scientific Discovery and a Sustainable Future. 2 - Riccardo Poli:
Super-Human and Super-AI Cognitive Augmentation of Human and Human-AI Teams Assisted by Brain Computer Interfaces. 3
Ant Colony Optimization and Swarm Intelligence
- Ahmed Almansoori, Muhanad Alkilabi, Elio Tuci:
On the evolution of mechanisms for three-option collective decision-making in a swarm of simulated robots. 4-12 - Tim Blackwell:
The Barrier Tree Benchmark: Many Basins and Double Funnels. 13-20 - Luigi Feola, Antoine Sion, Vito Trianni, Andreagiovanni Reina, Elio Tuci:
Aggregation Through Adaptive Random Walks in a Minimalist Robot Swarm. 21-29 - Kordel K. France, John W. Sheppard:
Factored Particle Swarm Optimization for Policy Co-training in Reinforcement Learning. 30-38 - Maryam Kebari, Annie S. Wu, H. David Mathias:
Pid-Inspired Modifications in Response Threshold Models In Swarm Intelligent Systems. 39-46 - Yi Liu, Jiang Qiu, Emma Hart, Yilan Yu, Zhongxue Gan, Wei Li:
Learning-Based Neural Ant Colony Optimization. 47-55 - Connor Mattson, Daniel S. Brown:
Leveraging Human Feedback to Evolve and Discover Novel Emergent Behaviors in Robot Swarms. 56-64 - Geoff Nitschke, Sindiso Mkhatshwa:
The Impact of Morphological Diversity in Robot Swarms. 65-74 - Giada Simionato, Federico A. Galatolo, Mario G. C. A. Cimino:
Swarms of Artificial Platelets for Emergent Hole Detection and Healing in Wireless Sensor Networks. 75-83 - Emilio Singh, Nelishia Pillay:
A Study of Ant-Based Pheromone Spaces for Generation Perturbative Hyper-Heuristics. 84-92 - Youwei Sun, Chaoli Sun:
Particle Swarm Optimization with Ring Topology for Multi-modal Multi-objective Problems. 93-101 - Tan-Lin Xiao, Qiang Yang, Xu-Dong Gao, Yuan-Yuan Ma, Zhenyu Lu, Sang-Woon Jeon, Jun Zhang:
Variation Encoded Large-Scale Swarm Optimizers for Path Planning of Unmanned Aerial Vehicle. 102-110 - Chi Zhang, Jian-Yu Li, Chun-Hua Chen, Yun Li, Zhi-Hui Zhan:
Region-based Evaluation Particle Swarm Optimization with Dual Solution Libraries for Real-time Traffic Signal Timing Optimization. 111-118
Complex Systems
- Raphaël Boige, Guillaume Richard, Jérémie Donà, Thomas Pierrot, Antoine Cully:
Gradient-Informed Quality Diversity for the Illumination of Discrete Spaces. 119-128 - François Cochevelou, David Leo Bonner, Martin-Pierre Schmidt:
Differentiable Soft-Robot Generation. 129-137 - Maxence Faldor, Félix Chalumeau, Manon Flageat, Antoine Cully:
MAP-Elites with Descriptor-Conditioned Gradients and Archive Distillation into a Single Policy. 138-146 - Caitlin Grasso, Josh C. Bongard:
Selection for short-term empowerment accelerates the evolution of homeostatic neural cellular automata. 147-155 - Luca Grillotti, Manon Flageat, Bryan Lim, Antoine Cully:
Don't Bet on Luck Alone: Enhancing Behavioral Reproducibility of Quality-Diversity Solutions in Uncertain Domains. 156-164 - Hannah Janmohamed, Thomas Pierrot, Antoine Cully:
Improving the Data Efficiency of Multi-Objective Quality-Diversity through Gradient Assistance and Crowding Exploration. 165-173 - Alican Mertan, Nick Cheney:
Modular Controllers Facilitate the Co-Optimization of Morphology and Control in Soft Robots. 174-183 - Giorgia Nadizar, Eric Medvet, Kathryn Walker, Sebastian Risi:
A Fully-distributed Shape-aware Neural Controller for Modular Robots. 184-192 - Atoosa Parsa, Sven Witthaus, Nidhi Pashine, Corey S. O'Hern, Rebecca Kramer-Bottiglio, Josh C. Bongard:
Universal Mechanical Polycomputation in Granular Matter. 193-201 - Alessandro Pierro, Kristine Heiney, Shamit Shrivastava, Giulia Marcucci, Stefano Nichele:
Optimization of a Hydrodynamic Computational Reservoir through Evolution. 202-210 - Federico Pigozzi, Stephanie J. Woodman, Eric Medvet, Rebecca Kramer-Bottiglio, Josh C. Bongard:
Morphology Choice Affects the Evolution of Affordance Detection in Robots. 211-219 - Bryon Tjanaka, Matthew C. Fontaine, David H. Lee, Yulun Zhang, Nivedit Reddy Balam, Nathaniel Dennler, Sujay S. Garlanka, Nikitas Dimitri Klapsis, Stefanos Nikolaidis:
pyribs: A Bare-Bones Python Library for Quality Diversity Optimization. 220-229
Evolutionary Combinatorial Optimization and Metaheuristics
- Firas Ben Jedidia, Benjamin Doerr, Martin S. Krejca:
Estimation-of-Distribution Algorithms for Multi-Valued Decision Variables. 230-238 - Jakob Bossek, Aneta Neumann, Frank Neumann:
On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem. 248-256 - Lorenzo Canonne, Bilel Derbel, Francisco Chicano, Gabriela Ochoa:
To Combine or not to Combine Graybox Crossover and Local Search? 257-265 - João Guilherme Cavalcanti Costa, Yi Mei, Mengjie Zhang:
Learning to Select Initialisation Heuristic for Vehicle Routing Problems. 266-274 - Francisco Chicano, Bilel Derbel, Sébastien Vérel:
Fourier Transform-based Surrogates for Permutation Problems. 275-283 - Francisco Chicano, Gabriela Ochoa, Bilel Derbel, Lorenzo Canonne:
Local Optima Markov Chain: A New Tool for Landscape-aware Analysis of Algorithm Dynamics. 284-292 - Ernestine Großmann, Sebastian Lamm, Christian Schulz, Darren Strash:
Finding Near-Optimal Weight Independent Sets at Scale. 293-302 - Miqing Li, Xiaofeng Han, Xiaochen Chu:
MOEAs Are Stuck in a Different Area at a Time. 303-311 - Alejandro Marrero, Eduardo Segredo, Emma Hart, Jakob Bossek, Aneta Neumann:
Generating diverse and discriminatory knapsack instances by searching for novelty in variable dimensions of feature-space. 312-320 - Florian Mischek, Nysret Musliu:
Leveraging problem-independent hyper-heuristics for real-world test laboratory scheduling. 321-329 - Napoleão Nepomuceno, Ricardo Barboza Saboia, André L. V. Coelho:
A MILP-Based Very Large-Scale Neighborhood Search for the Heterogeneous Vehicle Routing Problem with Simultaneous Pickup and Delivery. 330-338 - Jiyuan Pei, Hao Tong, Jialin Liu, Yi Mei, Xin Yao:
Local Optima Correlation Assisted Adaptive Operator Selection. 339-347 - Quan Minh Phan, Ngoc Hoang Luong:
Pareto Local Search is Competitive with Evolutionary Algorithms for Multi-Objective Neural Architecture Search. 348-356 - Jairo Enrique Ramírez Sánchez, Camilo Chacón Sartori, Christian Blum:
Q-Learning Ant Colony Optimization supported by Deep Learning for Target Set Selection. 357-366 - Valentino Santucci, Josu Ceberio:
Doubly Stochastic Matrix Models for Estimation of Distribution Algorithms. 367-374 - Manuel Torralbo, Leticia Hernando, Ernesto Contreras-Torres, José Antonio Lozano:
On the Use of Second Order Neighbors to Escape from Local Optima. 375-383 - Luyao Zhu, Fangfang Zhang, Xiaodong Zhu, Ke Chen, Mengjie Zhang:
Sample-Aware Surrogate-Assisted Genetic Programming for Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling. 384-392
Evolutionary Machine Learning
- Hayden Andersen, Andrew Lensen, Will N. Browne, Yi Mei:
Producing Diverse Rashomon Sets of Counterfactual Explanations with Niching Particle Swarm Optimization Algorithms. 393-401 - Ayhan Alp Aydeniz, Robert Tyler Loftin, Kagan Tumer:
Novelty Seeking Multiagent Evolutionary Reinforcement Learning. 402-410 - Victor Caetano, Matheus Cândido Teixeira, Gisele Lobo Pappa:
Symbolic Regression Trees as Embedded Representations. 411-419 - Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
Relieving Genetic Programming from Coefficient Learning for Symbolic Regression via Correlation and Linear Scaling. 420-428 - Joshua Cook, Kagan Tumer, Tristan Scheiner:
Leveraging Fitness Critics To Learn Robust Teamwork. 429-437 - Kaan Demir, Bach Hoai Nguyen, Bing Xue, Mengjie Zhang:
Co-operative Co-evolutionary Many-objective Embedded Multi-label Feature Selection with Decomposition-based PSO. 438-446 - Gaurav Dixit, Kagan Tumer:
Learning Synergies for Multi-Objective Optimization in Asymmetric Multiagent Systems. 447-455 - Matthew C. Fontaine, Stefanos Nikolaidis:
Covariance Matrix Adaptation MAP-Annealing. 456-465 - Nicolas Fontbonne, Nicolas Maudet, Nicolas Bredèche:
Adaptive Team Cooperative Co-Evolution for a Multi-Rover Distribution Problem. 466-475 - Lapo Frati, Neil Traft, Nick Cheney:
OmnImage: Evolving 1k Image Cliques for Few-Shot Learning. 476-484 - Ritam Guha, Wei Ao, Stephen Kelly, Vishnu Boddeti, Erik D. Goodman, Wolfgang Banzhaf, Kalyanmoy Deb:
MOAZ: A Multi-Objective AutoML-Zero Framework. 485-492 - Myeongjong Kang:
Positive Definite Nonparametric Regression using an Evolutionary Algorithm with Application to Covariance Function Estimation. 493-501 - Angus Kenny, Tapabrata Ray, Steffen Limmer, Hemant Kumar Singh, Tobias Rodemann, Markus Olhofer:
Hybridizing TPOT with Bayesian Optimization. 502-510 - William G. La Cava:
Optimizing fairness tradeoffs in machine learning with multiobjective meta-models. 511-519 - Pablo Moscato, Andrew Ciezak, Nasimul Noman:
Dynamic Depth for Better Generalization in Continued Fraction Regression. 520-528 - Ana Nikolikj, Saso Dzeroski, Mario Andrés Muñoz, Carola Doerr, Peter Korosec, Tome Eftimov:
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances. 529-537 - Lennart Schneider, Bernd Bischl, Janek Thomas:
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models. 538-547 - Hiroki Shiraishi, Yohei Hayamizu, Tomonori Hashiyama:
Fuzzy-UCS Revisited: Self-Adaptation of Rule Representations in Michigan-Style Learning Fuzzy-Classifier Systems. 548-557 - Stefano Tiso, Pedro Carvalho, Nuno Lourenço, Penousal Machado:
Biological insights on grammar-structured mutations improve fitness and diversity. 558-567 - Jamal Toutouh, Subhash Nalluru, Erik Hemberg, Una-May O'Reilly:
Semi-Supervised Learning with Coevolutionary Generative Adversarial Networks. 568-576 - Hai-Long Tran, Long Doan, Ngoc Hoang Luong, Huynh Thi Thanh Binh:
A Two-Stage Multi-Objective Evolutionary Reinforcement Learning Framework for Continuous Robot Control. 577-585 - Mathurin Videau, Nickolai Knizev, Alessandro Leite, Marc Schoenauer, Olivier Teytaud:
Interactive Latent Diffusion Model. 586-596 - Marcel Wever, Miran Özdogan, Eyke Hüllermeier:
Cooperative Co-Evolution for Ensembles of Nested Dichotomies for Multi-Class Classification. 597-605 - Naoya Yatsu, Hiroki Shiraishi, Hiroyuki Sato, Keiki Takadama:
Exploring High-dimensional Rules Indirectly via Latent Space Through a Dimensionality Reduction for XCS. 606-614 - Gonglin Yuan, Bing Xue, Mengjie Zhang:
An Effective One-Shot Neural Architecture Search Method with Supernet Fine-Tuning for Image Classification. 615-623 - Bowen Zheng, Ran Cheng:
Rethinking Population-assisted Off-policy Reinforcement Learning. 624-632
Evolutionary Multiobjective Optimization
- Guangyan An, Ziyu Wu, Zhilong Shen, Ke Shang, Hisao Ishibuchi:
Evolutionary Multi-Objective Deep Reinforcement Learning for Autonomous UAV Navigation in Large-Scale Complex Environments. 633-641 - Duc-Cuong Dang, Andre Opris, Bahare Salehi, Dirk Sudholt:
Analysing the Robustness of NSGA-II under Noise. 642-651 - Mohamed Gharafi, Nikolaus Hansen, Dimo Brockhoff, Rodolphe Le Riche:
Multiobjective Optimization with a Quadratic Surrogate-assisted CMA-ES. 652-660 - Cheng Gong, Yang Nan, Lie Meng Pang, Qingfu Zhang, Hisao Ishibuchi:
Effects of Including Optimal Solutions into Initial Population on Evolutionary Multiobjective Optimization. 661-669 - Linjun He, Yang Nan, Hisao Ishibuchi, Dipti Srinivasan:
Effects of Objective Space Normalization in Multi-Objective Evolutionary Algorithms on Real-World Problems. 670-678 - Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Effects of Dominance Modification on Hypervolume-based and IGD-based Performance Evaluation Results of NSGA-II. 679-687 - Yuhao Kang, Jialong Shi, Jianyong Sun, Ye Fan:
Improving Neighborhood Exploration Mechanism to Speed up PLS. 688-694 - Hsu Chen Liao, Wen Zhong Fang, Tian-Li Yu:
Adaptive Donor Selection Mixing for Multi-objective Optimization: an Enhanced Variant of MO-GOMEA. 695-703 - Arnaud Liefooghe, Manuel López-Ibáñez:
Many-objective (Combinatorial) Optimization is Easy. 704-712 - Arnaud Liefooghe, Gabriela Ochoa, Sébastien Vérel, Bilel Derbel:
Pareto Local Optimal Solutions Networks with Compression, Enhanced Visualization and Expressiveness. 713-721 - Yongfan Lu, Bingdong Li, Hong Qian, Wenjing Hong, Peng Yang, Aimin Zhou:
RM-SAEA: Regularity Model Based Surrogate-Assisted Evolutionary Algorithms for Expensive Multi-Objective Optimization. 722-730 - Frank Neumann, Carsten Witt:
3-Objective Pareto Optimization for Problems with Chance Constraints. 731-739 - Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi:
Two-Phase Procedure for Efficiently Removing Dominated Solutions From Large Solution Sets. 740-748 - Ryoji Tanabe:
On the Unbounded External Archive and Population Size in Preference-based Evolutionary Multi-objective Optimization Using a Reference Point. 749-758 - Michal Tomczyk, Milosz Kadzinski:
Co-evolution improves the efficiency of preference learning methods when the Decision Maker's aspirations develop over time. 759-767 - Yin Wu, Ruihao Zheng, Zhenkun Wang:
Decomposition-Based Multi-Objective Evolutionary Algorithm with Model-Based Ideal Point Estimation. 768-776 - Ying Wu, Na Yang, Long Chen, Ye Tian, Zhenzhou Tang:
Directed Quick Search Guided Evolutionary Algorithm for Large-scale Multi-objective Optimization Problems. 777-785 - Deepanshu Yadav, Palaniappan Ramu, Kalyanmoy Deb:
Multi-objective Robust Optimization and Decision-Making Using Evolutionary Algorithms. 786-794 - Na Yang, Quan Zhang, Ying Wu, Yisu Ge, Zhenzhou Tang:
A hierarchical clustering-based cooperative multi-population many-objective optimization algorithm. 795-803 - Han Zhu, Ke Shang, Hisao Ishibuchi:
STHV-Net: Hypervolume Approximation based on Set Transformer. 804-812
Evolutionary Numerical Optimization
- Gjorgjina Cenikj, Gasper Petelin, Carola Doerr, Peter Korosec, Tome Eftimov:
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems. 813-821 - Yuan Hong, Dirk Arnold:
Evolutionary Mixed-Integer Optimization with Explicit Constraints. 822-830 - Koki Ikeda, Isao Ono:
Natural Evolution Strategy for Mixed-Integer Black-Box Optimization. 831-838 - Masahiro Nomura, Youhei Akimoto, Isao Ono:
CMA-ES with Learning Rate Adaptation: Can CMA-ES with Default Population Size Solve Multimodal and Noisy Problems? 839-847 - Lisa Schönenberger, Hans-Georg Beyer:
On a Population Sizing Model for Evolution Strategies Optimizing the Highly Multimodal Rastrigin Function. 848-855 - André Thomaser, Jacob de Nobel, Diederick Vermetten, Furong Ye, Thomas Bäck, Anna V. Kononova:
When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems. 856-863 - Diederick Vermetten, Fabio Caraffini, Anna V. Kononova, Thomas Bäck:
Modular Differential Evolution. 864-872 - Diederick Vermetten, Furong Ye, Carola Doerr:
Using Affine Combinations of BBOB Problems for Performance Assessment. 873-881 - Yohei Watanabe, Kento Uchida, Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa:
(1+1)-CMA-ES with Margin for Discrete and Mixed-Integer Problems. 882-890
Genetic Algorithms
- Chenyang Bu, Zhiyong Cao, Chenlong He, Yuhong Zhang:
Probabilistic model with evolutionary optimization for cognitive diagnosis. 891-899 - João Correia, Vitor Pereira, Miguel Rocha:
Combining Evolutionary Algorithms with Reaction Rules Towards Focused Molecular Design. 900-909 - Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman:
The Impact of Asynchrony on Parallel Model-Based EAs. 910-918 - Alexandra Ivanova, Denis Antipov, Benjamin Doerr:
Larger Offspring Populations Help the (1 + (λ, λlambda)) Genetic Algorithm to Overcome the Noise. 919-928 - Robert Tjarko Lange, Tom Schaul, Yutian Chen, Chris Lu, Tom Zahavy, Valentin Dalibard, Sebastian Flennerhag:
Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization. 929-937 - Adel Nikfarjam, Ralf Rothenberger, Frank Neumann, Tobias Friedrich:
Evolutionary Diversity Optimisation in Constructing Satisfying Assignments. 938-945 - Michal Witold Przewozniczek, Renato Tinós, Marcin Michal Komarnicki:
First Improvement Hill Climber with Linkage Learning - on Introducing Dark Gray-Box Optimization into Statistical Linkage Learning Genetic Algorithms. 946-954 - Michal Witold Przewozniczek, Marcin Michal Komarnicki:
To slide or not to slide? Moving along fitness levels and preserving the gene subsets diversity in modern evolutionary computation. 955-962 - Ludovico Scarton, Alexander Hagg:
On the Suitability of Representations for Quality Diversity Optimization of Shapes. 963-971 - Hormoz Shahrzad, Risto P. Miikkulainen:
Accelerating Evolution Through Gene Masking and Distributed Search. 972-980 - Renato Tinós, Michal Przewozniczek, Darrell Whitley, Francisco Chicano:
Genetic Algorithm with Linkage Learning. 981-989
General Evolutionary Computation and Hybrids
- Benjamin Doerr, Arthur Dremaux, Johannes F. Lutzeyer, Aurélien Stumpf:
How the Move Acceptance Hyper-Heuristic Copes With Local Optima: Drastic Differences Between Jumps and Cliffs. 990-999 - Benjamin Doerr, Taha El Ghazi El Houssaini, Amirhossein Rajabi, Carsten Witt:
How Well Does the Metropolis Algorithm Cope With Local Optima? 1000-1008 - Steve Huntsman:
Quality-diversity in dissimilarity spaces. 1009-1018 - Paul Kent, Jürgen Branke:
Bayesian Quality Diversity Search with Interactive Illumination. 1019-1026 - Per Kristian Lehre, Mario Alejandro Hevia Fajardo, Jamal Toutouh, Erik Hemberg, Una-May O'Reilly:
Analysis of a Pairwise Dominance Coevolutionary Algorithm And DefendIt. 1027-1035 - Rajesh Pandian Muniasamy, Somesh Singh, Rupesh Nasre, N. S. Narayanaswamy:
Effective Parallelization of the Vehicle Routing Problem. 1036-1044 - Federico Pigozzi, Federico Julian Camerota Verdù, Eric Medvet:
How the Morphology Encoding Influences the Learning Ability in Body-Brain Co-Optimization. 1045-1054
Genetic Programming
- Evangelia Christodoulaki, Michael Kampouridis, Maria Kyropoulou:
Enhanced Strongly typed Genetic Programming for Algorithmic Trading. 1055-1063 - Fabrício Olivetti de França, Gabriel Kronberger:
Reducing Overparameterization of Symbolic Regression Models with Equality Saturation. 1064-1072 - Li Ding, Edward R. Pantridge, Lee Spector:
Probabilistic Lexicase Selection. 1073-1081 - Marko Durasevic, Francisco Javier Gil Gala, Domagoj Jakobovic:
Divide and conquer: Using single objective dispatching rules to improve convergence for multi-objective optimisation. 1082-1090 - Matheus Campos Fernandes, Fabrício Olivetti de França, Emilio Francesquini:
HOTGP - Higher-Order Typed Genetic Programming. 1091-1099 - Alcides Fonseca, Diogo Poças:
Comparing the expressive power of Strongly-Typed and Grammar-Guided Genetic Programming. 1100-1108 - Alina Geiger, Dominik Sobania, Franz Rothlauf:
Down-Sampled Epsilon-Lexicase Selection for Real-World Symbolic Regression Problems. 1109-1117 - Francisco Javier Gil Gala, Sezin Afsar, Marko Durasevic, Juan José Palacios, Murat Afsar:
Genetic programming for the vehicle routing problem with zone-based pricing. 1118-1126 - Joe Harrison, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman:
Mini-Batching, Gradient-Clipping, First- versus Second-Order: What Works in Gradient-Based Coefficient Optimisation for Symbolic Regression? 1127-1136 - Zhixing Huang, Yi Mei, Fangfang Zhang, Mengjie Zhang:
Grammar-guided Linear Genetic Programming for Dynamic Job Shop Scheduling. 1137-1145 - Vadim Liventsev, Anastasiia Grishina, Aki Härmä, Leon Moonen:
Fully Autonomous Programming with Large Language Models. 1146-1155 - Eric Medvet, Simone Pozzi, Luca Manzoni:
A General Purpose Representation and Adaptive EA for Evolving Graphs. 1156-1164 - Giorgia Nadizar, Fraser Garrow, Berfin Sakallioglu, Lorenzo Canonne, Sara Silva, Leonardo Vanneschi:
An Investigation of Geometric Semantic GP with Linear Scaling. 1165-1174 - Edward R. Pantridge, Thomas Helmuth:
Solving Novel Program Synthesis Problems with Genetic Programming using Parametric Polymorphism. 1175-1183 - Christian Raymond, Qi Chen, Bing Xue, Mengjie Zhang:
Fast and Efficient Local-Search for Genetic Programming Based Loss Function Learning. 1184-1193 - Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
A Double Lexicase Selection Operator for Bloat Control in Evolutionary Feature Construction for Regression. 1194-1202
Neuroevolution
- Bruno Gasperov, Marko Durasevic:
On Evolvability and Behavior Landscapes in Neuroevolutionary Divergent Search. 1203-1211 - Bryan Lim, Manon Flageat, Antoine Cully:
Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learning. 1212-1220 - Valentin Macé, Raphaël Boige, Félix Chalumeau, Thomas Pierrot, Guillaume Richard, Nicolas Perrin-Gilbert:
The Quality-Diversity Transformer: Generating Behavior-Conditioned Trajectories with Decision Transformers. 1221-1229 - Martín Naya-Varela, Andrés Faiña, Richard J. Duro:
Guiding the Exploration of the Solution Space in Walking Robots Through Growth-Based Morphological Development. 1230-1238 - Thai Huy Nguyen, Ngoc Hoang Luong:
Stable and Sample-Efficient Policy Search for Continuous Control via Hybridizing Phenotypic Evolutionary Algorithm with the Double Actors Regularized Critics. 1239-1247 - Joachim Winther Pedersen, Sebastian Risi:
Learning to Act through Evolution of Neural Diversity in Random Neural Networks. 1248-1256 - Yameng Peng, Andy Song, Vic Ciesielski, Haytham M. Fayek, Xiaojun Chang:
Fast Evolutionary Neural Architecture Search by Contrastive Predictor with Linear Regions. 1257-1266 - Sarah L. Thomson, Gabriela Ochoa, Nadarajen Veerapen, Krzysztof Michalak:
Channel Configuration for Neural Architecture: Insights from the Search Space. 1267-1275 - Jinglue Xu, Suryanarayanan N. A. V., Hitoshi Iba:
MPENAS: Multi-fidelity Predictor-guided Evolutionary Neural Architecture Search with Zero-cost Proxies. 1276-1285
Real World Applications
- Mohammad Majid al-Rifaie, Tim Blackwell:
Tomographic Reconstruction with Search Space Expansion. 1286-1293 - Georgios Andreadis, Peter A. N. Bosman, Tanja Alderliesten:
MOREA: a GPU-accelerated Evolutionary Algorithm for Multi-Objective Deformable Registration of 3D Medical Images. 1294-1302 - Peter J. Bentley, Soo Ling Lim, Paolo Arcaini, Fuyuki Ishikawa:
Using a Variational Autoencoder to Learn Valid Search Spaces of Safely Monitored Autonomous Robots for Last-Mile Delivery. 1303-1311 - Lukas Bostelmann-Arp, Christoph Steup, Sanaz Mostaghim:
Multi-Objective Seed Curve Optimization for Coverage Path Planning in Precision Farming. 1312-1320 - Gonzalo Carazo-Barbero, Eva Besada-Portas, José Luis Risco-Martín, José Antonio López Orozco:
EA-based ASV Trajectory Planner for Detecting Cyanobacterial Blooms in Freshwater. 1321-1329 - François Clément, Diederick Vermetten, Jacob de Nobel, Alexandre D. Jesus, Luís Paquete, Carola Doerr:
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms. 1330-1338 - Hinata Edo, Yoshiki Miyauchi, Atsuo Maki, Youhei Akimoto:
Trade-off Between Robustness and Worst-Case Performance in Min-Max Optimization. 1339-1347 - Diksha Goel, Aneta Neumann, Frank Neumann, Hung Nguyen, Mingyu Guo:
Evolving Reinforcement Learning Environment to Minimize Learner's Achievable Reward: An Application on Hardening Active Directory Systems. 1348-1356 - Matthew Hayslep, Edward C. Keedwell, Raziyeh Farmani:
Multi-Objective Multi-Gene Genetic Programming for the Prediction of Leakage in Water Distribution Networks. 1357-1364 - Daiki Kiribuchi, Ryoko Hatakeyama, Tomoshi Otsuki, Tatsuya Yoshioka, Kana Konno, Takumi Matsuda:
Combined Layout Optimization of Wind Farm and Cable Connection on Complex Terrain Using a Genetic Algorithm. 1365-1373 - Benjamin Kovács, Pierre Tassel, Martin Gebser:
Optimizing Dispatching Strategies for Semiconductor Manufacturing Facilities with Genetic Programming. 1374-1382 - Pier Luca Lanzi, Daniele Loiacono:
ChatGPT and Other Large Language Models as Evolutionary Engines for Online Interactive Collaborative Game Design. 1383-1390 - Matthew Lette, Kamrul Hasan Rahi, Hemant Kumar Singh, Tapabrata Ray:
Vertical-Axis Wind Turbine Design Using Surrogate-assisted Optimization with Physical Experiments In-loop. 1391-1399 - Piotr Lipinski:
Evolutionary Approach to Recommender Systems Improvement by Directory of Products Optimization. 1400-1408 - Jordan MacLachlan, Yi Mei, Fangfang Zhang, Mengjie Zhang, Jessica Signal:
Learning Emergency Medical Dispatch Policies Via Genetic Programming. 1409-1417 - Alejandro Medina, Melanie Richey, Mark Mueller, Jacob Schrum:
Evolving Flying Machines in Minecraft Using Quality Diversity. 1418-1426 - Vojtech Mrazek, Soyiba Jawed, Muhammad Arif, Aamir Saeed Malik:
Effective EEG Feature Selection for Interpretable MDD (Major Depressive Disorder) Classification. 1427-1435 - Aneta Neumann, Sharlotte Gounder, Xiankun Yan, Gregory Sherman, Benjamin Campbell, Mingyu Guo, Frank Neumann:
Diversity Optimization for the Detection and Concealment of Spatially Defined Communication Networks. 1436-1444 - Annibale Panichella, Giuseppe Di Domenico:
A Fast Multi-objective Evolutionary Approach for Designing Large-Scale Optical Mode Sorter. 1445-1453 - Magnus Eide Schjølberg, Nicklas Paus Bekkevold, Xavier F. C. Sánchez-Díaz, Ole Jakob Mengshoel:
Comparing Metaheuristic Optimization Algorithms for Ambulance Allocation: An Experimental Simulation Study. 1454-1463 - Alberto Tonda, Isabelle Alvarez, Sophie Martin, Giovanni Squillero, Evelyne Lutton:
Towards Evolutionary Control Laws for Viability Problems. 1464-1472 - Darrell Whitley, Ozeas Quevedo de Carvalho, Mark Roberts, Vivint Shetty, Piyabutra Jampathom:
Scheduling Multi-Resource Satellites using Genetic Algorithms and Permutation Based Representations. 1473-1481 - Daniel F. Zambrano-Gutierrez, Jorge Mario Cruz-Duarte, Herman Castañeda:
Automatic Hyper-Heuristic to Generate Heuristic-based Adaptive Sliding Mode Controller Tuners for Buck-Boost Converters. 1482-1489
Search-Based Software Engineering
- Leonhard Applis, Annibale Panichella, Ruben Marang:
Searching for Quality: Genetic Algorithms and Metamorphic Testing for Software Engineering ML. 1490-1498 - Matías Brizzio, Maxime Cordy, Mike Papadakis, César Sánchez, Nazareno Aguirre, Renzo Degiovanni:
Automated Repair of Unrealisable LTL Specifications Guided by Model Counting. 1499-1507 - Patric Feldmeier, Gordon Fraser:
Learning by Viewing: Generating Test Inputs for Games by Integrating Human Gameplay Traces in Neuroevolution. 1508-1517 - Teklit Gereziher, Selam Gebrekrstos, Gregory Gay:
Search-Based Test Generation Targeting Non-Functional Quality Attributes of Android Apps. 1518-1526 - Davide Li Calsi, Matias Duran, Thomas Laurent, Xiao-Yi Zhang, Paolo Arcaini, Fuyuki Ishikawa:
Adaptive Search-based Repair of Deep Neural Networks. 1527-1536
Theory
- Samuel Baguley, Tobias Friedrich, Aneta Neumann, Frank Neumann, Marcus Pappik, Ziena Zeif:
Fixed Parameter Multi-Objective Evolutionary Algorithms for the W-Separator Problem. 1537-1545 - Jakob Bossek, Dirk Sudholt:
Runtime Analysis of Quality Diversity Algorithms. 1546-1554 - Benjamin Doerr, Andrew James Kelley:
Fourier Analysis Meets Runtime Analysis: Precise Runtimes on Plateaus. 1555-1564 - Carola Doerr, Duri Andrea Janett, Johannes Lengler:
Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions. 1565-1574 - Emily L. Dolson:
Calculating lexicase selection probabilities is NP-Hard. 1575-1583 - Tobias Friedrich, Timo Kötzing, Aneta Neumann, Frank Neumann, Aishwarya Radhakrishnan:
Analysis of (1+1) EA on LeadingOnes with Constraints. 1584-1592 - Mario Alejandro Hevia Fajardo, Per Kristian Lehre:
How Fitness Aggregation Methods Affect the Performance of Competitive CoEAs on Bilinear Problems. 1593-1601 - Joost Jorritsma, Johannes Lengler, Dirk Sudholt:
Comma Selection Outperforms Plus Selection on OneMax with Randomly Planted Optima. 1602-1610 - Per Kristian Lehre, Andrew M. Sutton:
Runtime Analysis with Variable Cost. 1611-1618 - Per Kristian Lehre, Xiaoyu Qin:
Self-adaptation Can Help Evolutionary Algorithms Track Dynamic Optima. 1619-1627 - Johannes Lengler, Andre Opris, Dirk Sudholt:
Analysing Equilibrium States for Population Diversity. 1628-1636
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