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ORCIDGECCO 2018: Kyoto, Japan
- Hernán E. Aguirre, Keiki Takadama:
Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018. ACM 2018
Keynote talk
- Kazuo Yano:
AI for happiness of people. 1 - Tatsuya Okabe:
Exploitation of bio signal data to understand human state. 2 - Naoko Yamazaki:
Connecting human and technologies in space. 3 - David E. Goldberg:
On becoming a reflective practitioner. 4
Ant colony optimization and swarm intelligence
- Stephyn G. W. Butcher, John W. Sheppard
, Shane Strasser:
Information sharing and conflict resolution in distributed factored evolutionary algorithms. 5-12 - AbdElRahman A. ElSaid, Fatima El Jamiy, James Higgins, Brandon Wild, Travis Desell:
Using ant colony optimization to optimize long short-term memory recurrent neural networks. 13-20 - Jérôme Guzzi, Alessandro Giusti, Luca Maria Gambardella, Gianni A. Di Caro:
A model of artificial emotions for behavior-modulation and implicit coordination in multi-robot systems. 21-28 - Almuth Meier, Oliver Kramer:
Recurrent neural network-predictions for PSO in dynamic optimization. 29-36 - Bach Hoai Nguyen, Bing Xue, Peter Andreae:
A particle swarm optimization based feature selection approach to transfer learning in classification. 37-44 - Chaoli Sun, Yaochu Jin, Ying Tan:
Semi-supervised learning assisted particle swarm optimization of computationally expensive problems. 45-52 - Koen van der Blom, Thomas Bäck:
A new foraging-based algorithm for online scheduling. 53-60
Complex systems (artificial life/artificial immune systems/generative and developmental systems/evolutionary robotics/evolvable hardware)
- Jack Collins, Wade Geles, David Howard, Frédéric Maire:
Towards the targeted environment-specific evolution of robot components. 61-68 - Antoine Cully, Yiannis Demiris:
Hierarchical behavioral repertoires with unsupervised descriptors. 69-76 - Dominik Fischer, Sanaz Mostaghim, Larissa Albantakis:
How swarm size during evolution impacts the behavior, generalizability, and brain complexity of animats performing a spatial navigation task. 77-84 - Adam Gaier, Alexander Asteroth, Jean-Baptiste Mouret:
Data-efficient neuroevolution with kernel-based surrogate models. 85-92 - Daniele Gravina, Antonios Liapis, Georgios N. Yannakakis:
Fusing novelty and surprise for evolving robot morphologies. 93-100 - Emma Hart, Andreas S. W. Steyven, Ben Paechter:
Evolution of a functionally diverse swarm via a novel decentralised quality-diversity algorithm. 101-108 - Sam Kriegman, Nick Cheney, Francesco Corucci, Josh C. Bongard:
Interoceptive robustness through environment-mediated morphological development. 109-116 - Joel Lehman, Jay Chen, Jeff Clune, Kenneth O. Stanley:
Safe mutations for deep and recurrent neural networks through output gradients. 117-124 - Tønnes F. Nygaard, Charles P. Martin, Eivind Samuelsen, Jim Tørresen, Kyrre Glette:
Real-world evolution adapts robot morphology and control to hardware limitations. 125-132 - Dilini Samarasinghe, Erandi Lakshika, Michael Barlow, Kathryn Kasmarik:
Automatic synthesis of swarm behavioural rules from their atomic components. 133-140 - Tushar Semwal, Divya D. Kulkarni, Shivashankar B. Nair:
On an immuno-inspired distributed, embodied action-evolution cum selection algorithm. 141-148 - Vassilis Vassiliades, Jean-Baptiste Mouret:
Discovering the elite hypervolume by leveraging interspecies correlation. 149-156 - Frank Veenstra, Jonas Jørgensen, Sebastian Risi:
Evolution of fin undulation on a physical knifefish-inspired soft robot. 157-164 - Mostafa Wahby, Mary Katherine Heinrich, Daniel Nicolas Hofstadler, Payam Zahadat, Sebastian Risi, Phil Ayres, Thomas Schmickl, Heiko Hamann:
A robot to shape your natural plant: the machine learning approach to model and control bio-hybrid systems. 165-172 - Grant W. Woodford, Mathys C. du Plessis:
Robotic snake simulation using ensembles of artificial neural networks in evolutionary robotics. 173-180
Digital entertainment technologies and arts
- Fernando de Mesentier Silva, Julian Togelius, Frank Lantz, Andy Nealen:
Generating beginner heuristics for simple texas hold'em. 181-188 - Xun Li, Risto Miikkulainen:
Opponent modeling and exploitation in poker using evolved recurrent neural networks. 189-196 - Noriko Otani, Daisuke Okabe, Masayuki Numao:
Generating a melody based on symbiotic evolution for musicians' creative activities. 197-204 - Jacob Schrum:
Evolving indirectly encoded convolutional neural networks to play tetris with low-level features. 205-212 - Isabel Tweraser, Lauren E. Gillespie, Jacob Schrum:
Querying across time to interactively evolve animations. 213-220 - Vanessa Volz, Jacob Schrum, Jialin Liu, Simon M. Lucas, Adam M. Smith, Sebastian Risi:
Evolving mario levels in the latent space of a deep convolutional generative adversarial network. 221-228 - Dennis G. Wilson, Sylvain Cussat-Blanc, Hervé Luga, Julian F. Miller:
Evolving simple programs for playing atari games. 229-236
Evolutionary combinatorial optimization and metaheuristics
- Arben Ahmeti, Nysret Musliu:
Min-conflicts heuristic for multi-mode resource-constrained projects scheduling. 237-244 - Matheus de Freitas Araujo, José Elias C. Arroyo, Ricardo G. Tavares:
An effective hybrid meta-heuristic for a heterogeneous flow shop scheduling problem. 245-252 - Andreas Beham, Stefan Wagner, Michael Affenzeller:
Algorithm selection on generalized quadratic assignment problem landscapes. 253-260 - Julio Juárez, Carlos A. Brizuela:
A multi-objective formulation of the team formation problem in social networks: preliminary results. 261-268 - Francisco Chicano, Gabriela Ochoa, L. Darrell Whitley, Renato Tinós:
Enhancing partition crossover with articulation points analysis. 269-276 - Mohamed El Yafrani, Marcella S. R. Martins, Mehdi El Krari, Markus Wagner, Myriam Regattieri de Biase da Silva Delgado, Belaïd Ahiod, Ricardo Lüders:
A fitness landscape analysis of the travelling thief problem. 277-284 - Miguel A. Fernández Romero, Eric Alfredo Rincón García, Antonin Ponsich, Román Mora Gutiérrez:
A heuristic algorithm based on tabu search for the solution of flexible job shop scheduling problems with lot streaming. 285-292 - Tobias Friedrich, Francesco Quinzan, Markus Wagner:
Escaping large deceptive basins of attraction with heavy-tailed mutation operators. 293-300 - Tobias Friedrich, Timo Kötzing, Francesco Quinzan, Andrew M. Sutton:
Improving the run time of the (1 + 1) evolutionary algorithm with luby sequences. 301-308 - Wanru Gao, Tobias Friedrich, Frank Neumann, Christian Hercher:
Randomized greedy algorithms for covering problems. 309-315 - Angus Kenny, Xiaodong Li, Andreas T. Ernst:
A merge search algorithm and its application to the constrained pit problem in mining. 316-323 - Arnaud Liefooghe, Manuel López-Ibáñez, Luís Paquete, Sébastien Vérel:
Dominance, epsilon, and hypervolume local optimal sets in multi-objective optimization, and how to tell the difference. 324-331 - Orlando Moreira, Merten Popp, Christian Schulz:
Evolutionary multi-level acyclic graph partitioning. 332-339 - Petrica C. Pop, Oliviu Matei, Camelia-Mihaela Pintea:
A two-level diploid genetic based algorithm for solving the family traveling salesman problem. 340-346 - Robin Andre, Sebastian Schlag, Christian Schulz:
Memetic multilevel hypergraph partitioning. 347-354 - David Simoncini, Sophie Barbe, Thomas Schiex, Sébastien Vérel:
Fitness landscape analysis around the optimum in computational protein design. 355-362 - Daniel Sroka, Tomasz P. Pawlak:
One-class constraint acquisition with local search. 363-370 - Sarah L. Thomson, Sébastien Vérel, Gabriela Ochoa, Nadarajen Veerapen, David E. Cairns:
Multifractality and dimensional determinism in local optima networks. 371-378 - Hande Öztop, Mehmet Fatih Tasgetiren, Deniz Türsel Eliiyi, Quan-Ke Pan:
Iterated greedy algorithms for the hybrid flowshop scheduling with total flow time minimization. 379-385
Evolutionary machine learning
- Shawn L. E. Beaulieu, Sam Kriegman, Josh C. Bongard:
Combating catastrophic forgetting with developmental compression. 386-393 - Changwei Cai, Shuangrong Liu, Lin Wang, Bo Yang, Zhenxiang Chen, Jin Zhou:
Optimizing floating centroids method neural network classifier using dynamic multilayer particle swarm optimization. 394-401 - Boyuan Chen, Harvey Wu, Warren Mo, Ishanu Chattopadhyay, Hod Lipson:
Autostacker: a compositional evolutionary learning system. 402-409 - Matthew Dale:
Neuroevolution of hierarchical reservoir computers. 410-417 - Grant Dick, Caitlin A. Owen, Peter A. Whigham:
Evolving bagging ensembles using a spatially-structured niching method. 418-425 - Stefan Elfwing, Eiji Uchibe, Kenji Doya:
Online meta-learning by parallel algorithm competition. 426-433 - Unai Garciarena, Roberto Santana, Alexander Mendiburu:
Evolved GANs for generating pareto set approximations. 434-441 - Enrico Guiraud, Jakob Drefs, Jörg Lücke:
Evolutionary expectation maximization. 442-449 - Joel Lehman, Jay Chen, Jeff Clune, Kenneth O. Stanley:
ES is more than just a traditional finite-difference approximator. 450-457 - Andrew Lensen, Bing Xue, Mengjie Zhang:
Automatically evolving difficult benchmark feature selection datasets with genetic programming. 458-465 - Jason Zhi Liang, Elliot Meyerson, Risto Miikkulainen:
Evolutionary architecture search for deep multitask networks. 466-473 - Tyler McDonnell, Sari Andoni, Elmira Bonab, Sheila Cheng, Jun-Hwan Choi, Jimmie Goode, Keith Moore, Gavin Sellers, Jacob Schrum:
Divide and conquer: neuroevolution for multiclass classification. 474-481 - Masaya Nakata, Will N. Browne, Tomoki Hamagami:
Theoretical adaptation of multiple rule-generation in XCS. 482-489 - Yiming Peng, Gang Chen, Harman Singh, Mengjie Zhang:
NEAT for large-scale reinforcement learning through evolutionary feature learning and policy gradient search. 490-497 - Clara Pizzuti, Annalisa Socievole:
A genetic algorithm for finding an optimal curing strategy for epidemic spreading in weighted networks. 498-504 - Pablo Ribalta Lorenzo, Jakub Nalepa:
Memetic evolution of deep neural networks. 505-512 - Alejandro Rosales-Pérez, Andrés Eduardo Gutiérrez-Rodríguez, Salvador García, Hugo Terashima-Marín, Carlos A. Coello Coello, Francisco Herrera:
Cooperative multi-objective evolutionary support vector machines for multiclass problems. 513-520 - Cameron Shand, Richard Allmendinger, Julia Handl, John Keane:
Towards an adaptive encoding for evolutionary data clustering. 521-528 - Dominik Sobania, Franz Rothlauf:
CovSel: A new approach for ensemble selection applied to symbolic regression problems. 529-536 - Anthony Stein, Simon Menssen, Jörg Hähner:
What about interpolation?: a radial basis function approach to classifier prediction modeling in XCSF. 537-544 - Eiji Uchibe:
Efficient sample reuse in policy search by multiple importance sampling. 545-552 - Ryan J. Urbanowicz, Christopher Lo, John H. Holmes, Jason H. Moore:
Attribute tracking: strategies towards improved detection and characterization of complex associations. 553-560 - Marcel Wever, Felix Mohr, Eyke Hüllermeier:
Ensembles of evolved nested dichotomies for classification. 561-568 - Anil Yaman, Decebal Constantin Mocanu, Giovanni Iacca, George H. L. Fletcher, Mykola Pechenizkiy:
Limited evaluation cooperative co-evolutionary differential evolution for large-scale neuroevolution. 569-576 - Boyu Zhang, A. Kai Qin, Timos Sellis:
Evolutionary feature subspaces generation for ensemble classification. 577-584
Evolutionary multiobjective optimization
- Jakob Bossek, Christian Grimme, Stephan Meisel, Günter Rudolph, Heike Trautmann:
Local search effects in bi-objective orienteering. 585-592 - Maxim Buzdalov:
Generalized offline orthant search: one code for many problems in multiobjective optimization. 593-600 - Leilei Cao, Lihong Xu, Erik D. Goodman, Shuwei Zhu, Hui Li:
A differential prediction model for evolutionary dynamic multiobjective optimization. 601-608 - Tinkle Chugh, Richard Allmendinger, Vesa Ojalehto, Kaisa Miettinen:
Surrogate-assisted evolutionary biobjective optimization for objectives with non-uniform latencies. 609-616 - Bilel Derbel, Arnaud Liefooghe, Qingfu Zhang, Sébastien Vérel, Hernán E. Aguirre, Kiyoshi Tanaka:
A set-oriented MOEA/D. 617-624 - João A. Duro, Yiming Yan, Robin C. Purshouse, Peter J. Fleming:
Collaborative multi-objective optimization for distributed design of complex products. 625-632 - Jesús Guillermo Falcón-Cardona, Carlos A. Coello Coello:
A multi-objective evolutionary hyper-heuristic based on multiple indicator-based density estimators. 633-640 - Lucas R. C. de Farias, Pedro H. M. Braga, Hansenclever de F. Bassani, Aluizio F. R. Araújo:
MOEA/D with uniformly randomly adaptive weights. 641-648 - Bogdan Filipic, Tea Tusar:
A taxonomy of methods for visualizing pareto front approximations. 649-656 - Naoki Hamada, Keisuke Goto:
Data-driven analysis of pareto set topology. 657-664 - Hisao Ishibuchi, Takefumi Fukase, Naoki Masuyama, Yusuke Nojima:
Dual-grid model of MOEA/D for evolutionary constrained multiobjective optimization. 665-672 - Shouyong Jiang, Marcus Kaiser, Jinglei Guo, Shengxiang Yang, Natalio Krasnogor:
Less detectable environmental changes in dynamic multiobjective optimisation. 673-680 - Xiangming Jiang, Maoguo Gong, Tao Zhan, Zedong Tang:
Multiobjective sparse unmixing approach with noise removal. 681-688 - Oliver P. H. Jones, Jeremy E. Oakley, Robin C. Purshouse:
Component-level study of a decomposition-based multi-objective optimizer on a limited evaluation budget. 689-696 - Toshiki Kondo, Tomoaki Tatsukawa:
Efficient search techniques using adaptive discretization of design variables on real-coded evolutionary computations. 697-704 - Ngoc Hoang Luong, Tanja Alderliesten, Peter A. N. Bosman:
Improving the performance of MO-RV-GOMEA on problems with many objectives using tchebycheff scalarizations. 705-712 - Edgar Manoatl López, Carlos A. Coello Coello:
An improved version of a reference-based multi-objective evolutionary algorithm based on IGD+. 713-720 - Minami Miyakawa, Hiroyuki Sato, Yuji Sato:
Directed mating in decomposition-based MOEA for constrained many-objective optimization. 721-728 - Frederick Sander, Heiner Zille, Sanaz Mostaghim:
Transfer strategies from single- to multi-objective grouping mechanisms. 729-736 - Claudio Sanhueza, Francia Jiménez, Regina Berretta, Pablo Moscato:
mQAPViz: a divide-and-conquer multi-objective optimization algorithm to compute large data visualizations. 737-744 - Ke Shang, Hisao Ishibuchi, Min-Ling Zhang, Yiping Liu:
A new R2 indicator for better hypervolume approximation. 745-752 - Jialong Shi, Qingfu Zhang, Bilel Derbel, Arnaud Liefooghe, Jianyong Sun:
Parallel pareto local search revisited: first experimental results on bi-objective UBQP. 753-760 - Kendall Taylor, Xiaodong Li:
Interactive multiobjective optimisation: preference changes and algorithm responsiveness. 761-768 - Cheryl Sze Yin Wong, Suresh Sundaram:
Preference-based 3-dimensional en-route airspace sectorization. 769-776 - Junhua Wu, Sergey Polyakovskiy, Markus Wagner, Frank Neumann:
Evolutionary computation plus dynamic programming for the bi-objective travelling thief problem. 777-784 - Ying Xu, Yan Zhou:
A steady-state NSGA-II based multi-objective multicast routing algorithm for optical networks. 785-792 - Alexandru-Ciprian Zavoianu, Susanne Saminger-Platz, Edwin Lughofer, Wolfgang Amrhein:
Two enhancements for improving the convergence speed of a robust multi-objective coevolutionary algorithm. 793-800
Evolutionary numerical optimization
- Youhei Akimoto, Anne Auger, Tobias Glasmachers:
Drift theory in continuous search spaces: expected hitting time of the (1 + 1)-ES with 1/5 success rule. 801-808 - Chun-Kit Au, Ho-fung Leung:
Analysis of evolution strategies with the optimal weighted recombination. 809-816 - Sunith Bandaru, Amos H. C. Ng:
An empirical comparison of metamodeling strategies in noisy environments. 817-824 - Mariusz Bujny, Nikola Aulig, Markus Olhofer, Fabian Duddeck:
Learning-based topology variation in evolutionary level set topology optimization. 825-832 - An Chen, Yipeng Zhang, Zhigang Ren, Yang Yang, Yongsheng Liang, Bei Pang:
A global information based adaptive threshold for grouping large scale optimization problems. 833-840 - Thomas Gabor, Lenz Belzner, Claudia Linnhoff-Popien:
Inheritance-based diversity measures for explicit convergence control in evolutionary algorithms. 841-848 - Unai Garciarena, Roberto Santana, Alexander Mendiburu:
Expanding variational autoencoders for learning and exploiting latent representations in search distributions. 849-856 - S. C. Maree, Tanja Alderliesten, Dirk Thierens, Peter A. N. Bosman:
Real-valued evolutionary multi-modal optimization driven by hill-valley clustering. 857-864 - Kouhei Nishida, Youhei Akimoto:
PSA-CMA-ES: CMA-ES with population size adaptation. 865-872 - Tomasz P. Pawlak:
Performance improvements for evolutionary strategy-based one-class constraint synthesis. 873-880 - Eduardo Segredo, Eduardo Lalla-Ruiz, Emma Hart:
A novel similarity-based mutant vector generation strategy for differential evolution. 881-888 - Yuan Sun, Mohammad Nabi Omidvar, Michael Kirley, Xiaodong Li:
Adaptive threshold parameter estimation with recursive differential grouping for problem decomposition. 889-896 - Kento Uchida, Shinichi Shirakawa, Youhei Akimoto:
Analysis of information geometric optimization with isotropic gaussian distribution under finite samples. 897-904
Genetic algorithms
- Miguel A. Boland, Leandro Soares Indrusiak:
Analysis of the use of genetic algorithms for indoor localisation via cloud point matching. 905-912 - Chia-Sheng Chen, Hung-Wei Hsu, Tian-Li Yu:
Fast algorithm for fair