default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCID16th PPSN 2020: Leiden, The Netherlands - Part II
- Thomas Bäck
, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann:
Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II. Lecture Notes in Computer Science 12270, Springer 2020, ISBN 978-3-030-58114-5
Genetic Programming
- Amín V. Bernabé Rodríguez, Carlos A. Coello Coello:
Generation of New Scalarizing Functions Using Genetic Programming. 3-17 - Alcides Fonseca, Paulo Santos, Sara Silva:
The Usability Argument for Refinement Typed Genetic Programming. 18-32 - David Lynch, James McDermott, Michael O'Neill:
Program Synthesis in a Continuous Space Using Grammars and Variational Autoencoders. 33-47 - Lino Rodriguez-Coayahuitl, Alicia Morales-Reyes, Hugo Jair Escalante, Carlos A. Coello Coello:
Cooperative Co-Evolutionary Genetic Programming for High Dimensional Problems. 48-62 - Stefano Ruberto, Valerio Terragni, Jason H. Moore:
Image Feature Learning with Genetic Programming. 63-78 - Marco Virgolin, Andrea De Lorenzo, Eric Medvet, Francesca Randone:
Learning a Formula of Interpretability to Learn Interpretable Formulas. 79-93
Landscape Analysis
- Brahim Aboutaib, Sébastien Vérel, Cyril Fonlupt, Bilel Derbel, Arnaud Liefooghe, Belaïd Ahiod:
On Stochastic Fitness Landscapes: Local Optimality and Fitness Landscape Analysis for Stochastic Search Operators. 97-110 - Marko Durasevic, Domagoj Jakobovic, Marcella Scoczynski Ribeiro Martins, Stjepan Picek, Markus Wagner:
Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming Featuring Feynman Equations. 111-124 - Gabriela Ochoa, Francisco Chicano, Marco Tomassini:
Global Landscape Structure and the Random MAX-SAT Phase Transition. 125-138 - Quentin Renau, Carola Doerr, Johann Dréo, Benjamin Doerr:
Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy. 139-153 - Lennart Schäpermeier, Christian Grimme, Pascal Kerschke:
One PLOT to Show Them All: Visualization of Efficient Sets in Multi-objective Landscapes. 154-167
Multi-objective Optimization
- Lucas de Almeida Ribeiro, Michael Emmerich, Anderson da Silva Soares, Telma Woerle de Lima:
On Sharing Information Between Sub-populations in MOEA/S. 171-185 - Timo M. Deist, Stefanus C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Multi-objective Optimization by Uncrowded Hypervolume Gradient Ascent. 186-200 - Jesús Guillermo Falcón-Cardona, Arnaud Liefooghe, Carlos A. Coello Coello:
An Ensemble Indicator-Based Density Estimator for Evolutionary Multi-objective Optimization. 201-214 - Stefanus C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Ensuring Smoothly Navigable Approximation Sets by Bézier Curve Parameterizations in Evolutionary Bi-objective Optimization. 215-228 - Zhilei Ren, Shaozheng Dong, Xiaochen Li, Zongzheng Chi, He Jiang:
Many-Objective Test Database Generation for SQL. 229-242 - Bhupinder Singh Saini, Jussi Hakanen, Kaisa Miettinen:
A New Paradigm in Interactive Evolutionary Multiobjective Optimization. 243-256 - Ke Shang, Hisao Ishibuchi, Weiyu Chen, Lukás Adam:
Hypervolume Optimal μ-Distributions on Line-Based Pareto Fronts in Three Dimensions. 257-270 - Lei Sun, Ke Li:
Adaptive Operator Selection Based on Dynamic Thompson Sampling for MOEA/D. 271-284 - Diana Cristina Valencia-Rodríguez, Carlos A. Coello Coello:
A Study of Swarm Topologies and Their Influence on the Performance of Multi-Objective Particle Swarm Optimizers. 285-298 - Mathew J. Walter, David J. Walker, Matthew J. Craven:
Visualising Evolution History in Multi- and Many-objective Optimisation. 299-312 - Yali Wang, André H. Deutz, Thomas Bäck, Michael Emmerich:
Improving Many-Objective Evolutionary Algorithms by Means of Edge-Rotated Cones. 313-326
Real-World Applications
- Mahfouth Alghamdi, Christoph Treude, Markus Wagner:
Human-Like Summaries from Heterogeneous and Time-Windowed Software Development Artefacts. 329-342 - Claude Carlet, Marko Djurasevic, Domagoj Jakobovic, Stjepan Picek:
A Search for Additional Structure: The Case of Cryptographic S-boxes. 343-356 - Tim Cofala, Lars Elend, Philip Mirbach, Jonas Prellberg, Thomas Teusch, Oliver Kramer:
Evolutionary Multi-objective Design of SARS-CoV-2 Protease Inhibitor Candidates. 357-371 - Marcin Czajkowski, Krzysztof Jurczuk, Marek Kretowski:
Generic Relative Relations in Hierarchical Gene Expression Data Classification. 372-384 - Thomas Kaufmann, Matthias Horn, Günther R. Raidl:
A Variable Neighborhood Search for the Job Sequencing with One Common and Multiple Secondary Resources Problem. 385-398 - Krzysztof Michalak:
Evolutionary Graph-Based V+E Optimization for Protection Against Epidemics. 399-412 - Nicholas D. F. Ross, Ed Keedwell, Dragan A. Savic:
Human-Derived Heuristic Enhancement of an Evolutionary Algorithm for the 2D Bin-Packing Problem. 413-427 - Hao Tong, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao:
Towards Novel Meta-heuristic Algorithms for Dynamic Capacitated Arc Routing Problems. 428-440 - Marjolein C. van der Meer, Arjan Bel, Yury Niatsetski, Tanja Alderliesten, Bradley R. Pieters, Peter A. N. Bosman:
Robust Evolutionary Bi-objective Optimization for Prostate Cancer Treatment with High-Dose-Rate Brachytherapy. 441-453 - Han Zhang, Jialin Liu, Xin Yao:
A Hybrid Evolutionary Algorithm for Reliable Facility Location Problem. 454-467
Reinforcement Learning
- Jordan T. Bishop, Marcus Gallagher:
Optimality-Based Analysis of XCSF Compaction in Discrete Reinforcement Learning. 471-484 - Arina Buzdalova, Carola Doerr, Anna Rodionova:
Hybridizing the 1/5-th Success Rule with Q-Learning for Controlling the Mutation Rate of an Evolutionary Algorithm. 485-499 - Nathaniel du Preez-Wilkinson, Marcus Gallagher:
Fitness Landscape Features and Reward Shaping in Reinforcement Learning Policy Spaces. 500-514 - Nihat Engin Toklu, Pawel Liskowski, Rupesh Kumar Srivastava:
ClipUp: A Simple and Powerful Optimizer for Distribution-Based Policy Evolution. 515-527 - Hui Wang, Mike Preuss, Aske Plaat:
Warm-Start AlphaZero Self-play Search Enhancements. 528-542
Theoretical Aspects of Nature-Inspired Optimization
- Denis Antipov, Benjamin Doerr:
Runtime Analysis of a Heavy-Tailed (1+(λ , λ )) Genetic Algorithm on Jump Functions. 545-559 - Denis Antipov, Maxim Buzdalov, Benjamin Doerr:
First Steps Towards a Runtime Analysis When Starting with a Good Solution. 560-573 - Maxim Buzdalov, Carola Doerr:
Optimal Mutation Rates for the (1+λ ) EA on OneMax. 574-587 - Anh Viet Do, Frank Neumann:
Maximizing Submodular or Monotone Functions Under Partition Matroid Constraints by Multi-objective Evolutionary Algorithms. 588-603 - Benjamin Doerr:
Lower Bounds for Non-elitist Evolutionary Algorithms via Negative Multiplicative Drift. 604-618 - Benjamin Doerr:
Exponential Upper Bounds for the Runtime of Randomized Search Heuristics. 619-633 - Zhengxin Huang, Zefeng Chen, Yuren Zhou:
Analysis on the Efficiency of Multifactorial Evolutionary Algorithms. 634-647 - Timo Kötzing, Carsten Witt:
Improved Fixed-Budget Results via Drift Analysis. 648-660 - Laurent Meunier, Yann Chevaleyre, Jérémy Rapin, Clément W. Royer, Olivier Teytaud:
On Averaging the Best Samples in Evolutionary Computation. 661-674 - Sumit Mishra, Maxim Buzdalov:
Filter Sort Is $\varOmega (N^3)$ in the Worst Case. 675-685 - Andrew M. Sutton, L. Darrell Whitley:
Approximation Speed-Up by Quadratization on LeadingOnes. 686-698 - Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
Benchmarking a (μ +λ ) Genetic Algorithm with Configurable Crossover Probability. 699-713
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2025-01-23 20:37 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
