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18th PPSN 2024: Hagenberg, Austria - Part III
- Michael Affenzeller, Stephan M. Winkler, Anna V. Kononova, Heike Trautmann, Tea Tusar, Penousal Machado, Thomas Bäck:
Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part III. Lecture Notes in Computer Science 15150, Springer 2024, ISBN 978-3-031-70070-5
Theoretical Aspects of Nature-Inspired Optimization
- Johannes Lengler, Konstantin Sturm:
Self-adjusting Evolutionary Algorithms are Slow on a Class of Multimodal Landscapes. 3-18 - Denis Antipov, Aneta Neumann, Frank Neumann, Andrew M. Sutton:
Runtime Analysis of Evolutionary Diversity Optimization on a Tri-Objective Version of the (LeadingOnes, TrailingZeros) Problem. 19-35 - Frank Neumann, Carsten Witt:
Sliding Window 3-Objective Pareto Optimization for Problems with Chance Constraints. 36-52 - Sumit Adak, Carsten Witt:
Runtime Analysis of a Multi-valued Compact Genetic Algorithm on Generalized OneMax. 53-69 - Cella Florescu, Marc Kaufmann, Johannes Lengler, Ulysse Schaller:
Faster Optimization Through Genetic Drift. 70-85 - Denis Antipov, Timo Kötzing, Aishwarya Radhakrishnan:
Greedy Versus Curious Parent Selection for Multi-objective Evolutionary Algorithms. 86-101 - Sacha Cerf, Johannes Lengler:
How Population Diversity Influences the Efficiency of Crossover. 102-116 - Per Kristian Lehre, Shishen Lin:
Overcoming Binary Adversarial Optimisation with Competitive Coevolution. 117-132 - Jiwon Lee, Andrew M. Sutton:
Evolving Populations of Solved Subgraphs with Crossover and Constraint Repair. 133-148 - Jonathan Gadea Harder, Aneta Neumann, Frank Neumann:
Analysis of Evolutionary Diversity Optimisation for the Maximum Matching Problem. 149-165 - Frank Neumann, Günter Rudolph:
Archive-Based Single-Objective Evolutionary Algorithms for Submodular Optimization. 166-180 - Denis Antipov, Aneta Neumann, Frank Neumann:
Local Optima in Diversity Optimization: Non-trivial Offspring Population is Essential. 181-196 - Benjamin Doerr, Martin S. Krejca, Noé Weeks:
Proven Runtime Guarantees for How the MOEA/D: Computes the Pareto Front from the Subproblem Solutions. 197-212 - Mario Alejandro Hevia Fajardo, Per Kristian Lehre:
Ranking Diversity Benefits Coevolutionary Algorithms on an Intransitive Game. 213-229 - Duc-Cuong Dang, Andre Opris, Dirk Sudholt:
On the Equivalence Between Stochastic Tournament and Power-Law Ranking Selection and How to Implement Them Efficiently. 230-245 - Duc-Cuong Dang, Andre Opris, Dirk Sudholt:
Level-Based Theorems for Runtime Analysis of Multi-objective Evolutionary Algorithms. 246-263 - Renzhong Deng, Weijie Zheng, Mingfeng Li, Jie Liu, Benjamin Doerr:
Runtime Analysis for State-of-the-Art Multi-objective Evolutionary Algorithms on the Subset Selection Problem. 264-279 - Mingfeng Li, Weijie Zheng, Wen Xie, Ao Sun, Xin Yao:
When Does the Time-Linkage Property Help Optimization by Evolutionary Algorithms? 280-294 - Shengjie Ren, Chao Bian, Miqing Li, Chao Qian:
A First Running Time Analysis of the Strength Pareto Evolutionary Algorithm 2 (SPEA2). 295-312
(Evolutionary) Machine Learning and Neuroevolution
- Gijs Schröder, Inge M. N. Wortel, Johannes Textor:
Population-Based Algorithms Built on Weighted Automata. 315-332 - Shoffan Saifullah, Rafal Drezewski:
Automatic Brain Tumor Segmentation Using Convolutional Neural Networks: U-Net Framework with PSO-Tuned Hyperparameters. 333-351 - Damy M. F. Ha, Tanja Alderliesten, Peter A. N. Bosman:
Learning Discretized Bayesian Networks with GOMEA. 352-368 - Ganyuan Luo, Hao Li, Zefeng Chen, Yuren Zhou:
Pareto-Informed Multi-objective Neural Architecture Search. 369-385 - Hiroki Shiraishi, Rongguang Ye, Hisao Ishibuchi, Masaya Nakata:
A Variable-Length Fuzzy Set Representation for Learning Fuzzy-Classifier Systems. 386-402
Evolvable Hardware and Evolutionary Robotics
- Babak Hosseinkhani Kargar, Karine Miras, A. E. Eiben:
Exploring Proprioceptive Feedback in the Evolution of Modular Robots. 405-418
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