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ORCIDGECCO 2014: Vancouver, BC, Canada - Companion Material
- Dirk V. Arnold, Enrique Alba:
Genetic and Evolutionary Computation Conference, GECCO '14, Vancouver, BC, Canada, July 12-16, 2014, Companion Material Proceedings. ACM 2014, ISBN 978-1-4503-2881-4
Keynotes and invited talk
- Yoshua Bengio:
Deep learning and cultural evolution. 1-2 - Dario Floreano:
Bridging natural and artificial evolution. 3-4 - Sumit Gulwani:
Applications of program synthesis to end-user programming and intelligent tutoring systems. 5-6
Track: ant colony optimization and swarm intelligence
- Ya-Hui Jia, Wei-Neng Chen, Xiaomin Hu:
A PSO approach for software project planning. 7-8 - Malte Langosz
, Kai Alexander von Szadkowski, Frank Kirchner:
Introducing particle swarm optimization into a genetic algorithm to evolve robot controllers. 9-10 - Xing Liu, Lin Shang:
Fitness proportionate selection based binary particle swarm optimization. 11-12 - Christopher K. Monson, Kevin D. Seppi:
Under-informed momentum in PSO. 13-14 - Mengqi Peng, Yue-Jiao Gong, Jing-Jing Li, Ying-Biao Lin:
Multi-swarm particle swarm optimization with multiple learning strategies. 15-16 - Aymen Sioud, Caroline Gagné, Marc Gravel:
An ant colony optimization for solving a hybrid flexible flowshop. 17-18 - Qiuhang Tan, Hejun Wu, Biao Hu, Xingcheng Liu:
An improved artificial bee colony algorithm for clustering. 19-20
Track: artificial immune systems
- Nicola Capodieci, Emma Hart, Giacomo Cabri:
Artificial immune systems in the context of autonomic computing: integrating design paradigms. 21-22 - Yiqi Deng, Peter J. Bentley:
Adapting to dynamically changing noise during learning of heart sounds: an AIS-based approach using systemic computation. 23-24
Track: artificial life, robotics, and evolvable hardware
- Faith Agwang, Willem S. van Heerden, Geoff Nitschke:
Lifetimes of migration. 25-26 - Alan Blair:
Incremental evolution of HERCL programs for robust control. 27-28 - Martin Delecluse, Stéphane Sanchez, Sylvain Cussat-Blanc, Nicolas Schneider, Jean-Baptiste Welcomme:
High-level behavior regulation for multi-robot systems. 29-30 - Heiko Hamann:
Evolving prediction machines: collective behaviors based on minimal surprisal. 31-32 - Walter O. Krawec:
Minimal variable quantum decision makers for robotic control. 33-34 - Padmini Rajagopalan, Aditya Rawal, Kay E. Holekamp, Risto Miikkulainen:
General intelligence through prolonged evolution of densely connected neural networks. 35-36
Track: biological and biomedical applications
- Soha Ahmed, Mengjie Zhang, Lifeng Peng:
Prediction of detectable peptides in MS data using genetic programming. 37-38 - Vitoantonio Bevilacqua, Paolo Pannarale:
A semantic expert system for the evolutionary design of synthetic gene networks. 39-40 - Javier Garcia-Bernardo, Margaret J. Eppstein:
Evolving small GRNs with a top-down approach. 41-42 - Hongjian Li, Kwong-Sak Leung, Chun Ho Chan, Hei Lun Cheung, Man Hon Wong:
iSYN: de novo drug design with click chemistry support. 43-44
Track: digital entertainment technologies and arts
- Lucas Ferreira, Leonardo T. Pereira, Claudio Fabiano Motta Toledo:
A multi-population genetic algorithm for procedural generation of levels for platform games. 45-46 - Lucas Ferreira, Leonardo T. Pereira, Claudio Fabiano Motta Toledo, Rodrigo de Freitas Pereira:
Evolutionary approaches to evolve AI scripts for a RTS game. 47-48 - Rubén Héctor García-Ortega, Pablo García-Sánchez, Antonio Miguel Mora, Juan Julián Merelo Guervós:
A methodology for designing emergent literary backstories on non-player characters using genetic algorithms. 49-50 - Maxime Sanselone, Stéphane Sanchez, Cédric Sanza, David Panzoli, Yves Duthen:
Control of non player characters in a medical learning game with Monte Carlo tree search. 51-52
Track: estimation of distribution algorithms
- Chung-Yao Chuang, Stephen F. Smith:
Estimation of distribution algorithms based on n-gramstatistics for sequencing and optimization. 53-54 - Hadi Sharifi, Amin Nikanjam, Hossein Karshenas, Negar Najimi:
Complexity of model learning in EDAs: multi-structure problems. 55-56 - Bo Wang, Hua Xu, Yuan Yuan:
A two-level hierarchical EDA using conjugate priori. 57-58
Track: evolution strategies and evolutionary programming
- Walter O. Krawec:
An algorithm for evolving multiple quantum operators for arbitrary quantum computational problems. 59-60 - Jialin Liu, David Lupien St-Pierre, Olivier Teytaud:
A mathematically derived number of resamplings for noisy optimization. 61-62 - Juan Pablo Serrano Rubio, Arturo Hernández Aguirre, Rafael Herrera Guzmán:
SEA: an evolutionary algorithm based on spherical inversions. 63-64
Track: evolutionary combinatorial optimization and metaheuristics
- Peng Cheng, Jeng-Shyang Pan:
Use EMO to protect sensitive knowledge in association rule mining by adding items. 65-66 - Daniil Chivilikhin, Vladimir Ulyantsev:
Inferring automata-based programs from specification with mutation-based ant colony optimization. 67-68 - André L. Maravilha, Jaime A. Ramírez, Felipe Campelo:
Combinatorial optimization with differential evolution: a set-based approach. 69-70 - Richard J. Marshall, Mark Johnston, Mengjie Zhang:
Hyper-heuristics, grammatical evolution and the capacitated vehicle routing problem. 71-72 - Jean Paulo Martins, Humberto J. Longo, Alexandre C. B. Delbem:
On the effectiveness of genetic algorithms for the multidimensional knapsack problem. 73-74
Track: evolutionary machine learning
- Alessia Amelio, Clara Pizzuti:
Uncovering communities in multidimensional networks with multiobjective genetic algorithms. 75-76 - Daniel Lückehe, Oliver Kramer:
A variable kernel function for hybrid unsupervised kernel regression. 77-78 - Mina Moradi Kordmahalleh, Mohammad Gorji Sefidmazgi, Abdollah Homaifar, K. C. Dukka Bahadur, Anthony Guiseppi-Elie:
Time-series forecasting with evolvable partially connected artificial neural network. 79-80 - Danilo Vasconcellos Vargas, Hirotaka Takano, Junichi Murata:
Novelty-organizing classifiers applied to classification and reinforcement learning: towards flexible algorithms. 81-82 - Bing Xue, Wenlong Fu, Mengjie Zhang:
Differential evolution (DE) for multi-objective feature selection in classification. 83-84
Track: evolutionary multiobjective optimization
- Abir Chaabani, Slim Bechikh, Lamjed Ben Said:
An indicator-based chemical reaction optimization algorithm for multi-objective search. 85-86 - Wentao Guo, Xinjie Yu:
Non-dominated sorting differential evolution with improved directional convergence and spread for multiobjective optimization. 87-88 - Hisao Ishibuchi, Hiroyuki Masuda, Yusuke Nojima:
Meta-level multi-objective formulations of set optimization for multi-objective optimization problems: multi-reference point approach to hypervolume maximization. 89-90 - Kaname Narukawa, Yuki Tanigaki, Hisao Ishibuchi:
Evolutionary many-objective optimization using preference on hyperplane. 91-92 - Yutao Qi, Xiaoliang Ma, Minglei Yin, Fang Liu, Jingxuan Wei:
MOEA/D with a delaunay triangulation based weight adjustment. 93-94 - Pradyumn Kumar Shukla, Marlon Alexander Braun, Hartmut Schmeck:
On the interrelationships between knees and aggregate objective functions. 95-96 - Fugui Zhong, Bo Yuan, Bin Li:
Hybridization of NSGA-II with greedy re-assignment for variation tolerant logic mapping on nano-scale crossbar architectures. 97-98
Track: generative and developmental systems
- Ben Cole, Michael Muthukrishna:
Nu-life: spontaneous dynamic hierarchical organization in a non-uniform "life-like" cellular automata. 99-100 - Jean Disset, Sylvain Cussat-Blanc, Yves Duthen:
Toward organogenesis of artificial creatures. 101-102 - Phillip Verbancsics, Joshua Harguess:
Deep learning through generative and developmental system. 103-104
Track: genetic algorithms
- Daniel Cagara, Ana L. C. Bazzan, Björn Scheuermann:
Getting you faster to work: a genetic algorithm approach to the traffic assignment problem. 105-106 - Taku Hasegawa, Kaname Matsumura, Kaiki Tsuchie, Naoki Mori, Keinosuke Matsumoto:
Novel virtual fitness evaluation framework for fitness landscape learning evolutionary computation. 107-108 - Conor Higgins, Conor Ryan, Áine Kearns, Mikael Fernström:
The creation and facilitation of speech and language therapy sessions for individuals with aphasia. 109-110 - Xiao-ma Huang, Yue-Jiao Gong, Jing-Jing Li, Xiaomin Hu:
A novel genetic algorithm based on partitioning for large-scale network design problems. 111-112 - Kazuyuki Inoue, Naoki Mori, Keinosuke Matsumoto:
A novel genetic algorithm based on the life cycle of dictyostelium. 113-114 - Karthik Kuber, Stuart W. Card, Kishan G. Mehrotra, Chilukuri K. Mohan:
Ancestral networks in evolutionary algorithms. 115-116 - Ho Tat Lam, Kwok Yip Szeto:
Search for the most reliable network of fixed connectivity using genetic algorithm. 117-118 - Juan Julián Merelo Guervós, Pedro A. Castillo, Antonio Miguel Mora, Anna Isabel Esparcia-Alcázar, Víctor Manuel Rivas Santos:
Assessing different architectures for evolutionary algorithms in javascript. 119-120 - Janusz Orkisz, Maciej Glowacki:
On dedicated evolutionary algorithms for large non-linear constrained optimization problems. 121-122 - Ming Yang, Jing Guan, Zhihua Cai, Changhe Li:
A dimensional-level adaptive differential evolutionary algorithm for continuous optimization. 123-124 - Xin-yuan Zhang, Yue-jiao Gong, Jing-Jing Li, Ying Lin:
Evolutionary computation for lifetime maximization of wireless sensor networks in complex 3D environments. 125-126
Track: genetic programming
- R. Muhammad Atif Azad, David Medernach, Conor Ryan:
Efficient interleaved sampling of training data in genetic programming. 127-128 - Kevin M. Barresi:
Evolved nonlinear predictor functions for lossless image compression. 129-130 - Gopinath Chennupati, Conor Ryan, R. Muhammad Atif Azad:
Predict the success or failure of an evolutionary algorithm run. 131-132 - Adam T. S. Cohen, Tony White:
CityBreeder: city design with evolutionary computation. 133-134 - Léo Françoso Dal Piccol Sotto, Vinícius Veloso de Melo:
Comparison of linear genetic programming variants for symbolic regression. 135-136 - Marco Gaudesi, Giovanni Squillero, Alberto Paolo Tonda:
Universal information distance for genetic programming. 137-138 - Muhammad Rezaul Karim, Conor Ryan:
On improving grammatical evolution performance in symbolic regression with attribute grammar. 139-140 - William G. La Cava, Lee Spector, Kourosh Danai, Matthew Lackner:
Evolving differential equations with developmental linear genetic programming and epigenetic hill climbing. 141-142 - Andrea Mambrini, Luca Manzoni:
A comparison between geometric semantic GP and cartesian GP for boolean functions learning. 143-144 - Michael Richard Medland, Kyle Robert Harrison, Beatrice M. Ombuki-Berman:
Incorporating expert knowledge in object-oriented genetic programming. 145-146 - Lee Spector, Thomas Helmuth:
Effective simplification of evolved push programs using a simple, stochastic hill-climber. 147-148 - Guilherme Cesário Strachan, Adriano Soares Koshiyama, Douglas Mota Dias, Marley Maria Bernardes Rebuzzi Vellasco, Marco Aurélio Cavalcanti Pacheco:
Towards a quantum-inspired multi-gene linear genetic programming model. 149-150 - Seishi Takamura, Atsushi Shimizu:
GPGPU-assisted denoising filter generation for video coding. 151-152 - Yanyun Tao, Yuzhen Zhang, Lijun Zhang, Chao Gu:
A projection-based decomposition in EHW method for design of relatively large circuits. 153-154
Track: integrative genetic and evolutionary computation
- Manal T. Adham, Peter J. Bentley:
An artificial ecosystem algorithm applied to the travelling salesman problem. 155-156 - Michael Kirley, Friedrich Burkhard von der Osten:
Risk aversion and mobility in the public goods game. 157-158 - Jeffrey Tsang:
The structure of an 8-state finite transducer representation for prisoner's dilemma. 159-160 - Shujin Ye, Han Huang, Changjian Xu:
Enhancing the differential evolution with convergence speed controller for continuous optimization problems. 161-162
Track: parallel evolutionary systems
- Shikha Gupta, Naveen Kumar:
GPU-based massively parallel quantum inspired genetic algorithm for detection of communities in complex networks. 163-164
Track: real world applications
- Eric Yawei Chen, Lin-Shung Huang, Ole J. Mengshoel, Jason D. Lohn:
Darwin: a ground truth agnostic CAPTCHA generator using evolutionary algorithm. 165-166 - Peng Cheng, Jeng-Shyang Pan:
Completely hide sensitive association rules using EMO by deleting transactions. 167-168 - Amirali Darvishzadeh, Bir Bhanu:
Distributed multi-robot search in the real-world using modified particle swarm optimization. 169-170 - Walter O. Krawec:
Using evolutionary techniques to analyze the security of quantum key distribution protocols. 171-172 - Soumya D. Mohanty:
Detection and estimation of unmodeled narrowband nonstationary signals: application of particle swarm optimization in gravitational wave data analysis. 173-174 - Satoshi Ono, Takeru Maehara, Kentaro Nakai, Ryo Ikeda, Koutaro Taniguchi:
Semi-fragile watermark design for detecting illegal two-dimensional barcodes by evolutionary multi-objective optimization. 175-176 - Shana Schlottfeldt, Jon Timmis, Maria Emília M. T. Walter, André C. P. L. F. de Carvalho, José Alexandre Felizola Diniz-Filho, Lorena M. Simon, Rafael D. Loyola, Mariana P. C. Telles:
Multi-objective optimization applied to systematic conservation planning and spatial conservation priorities under climate change. 177-178 - Ervin Teng, Derek Kozel, Bob Iannucci, Jason D. Lohn:
Evolution of digital modulation schemes for radio systems. 179-180 - Charlie Vanaret, Nicolas Durand, Jean-Marc Alliot:
Windmill farm pattern optimization using evolutionary algorithms. 181-182 - Guang-Wei Zhang, Zhi-Hui Zhan, Ke-Jing Du, Wei-Neng Chen:
Normalization group brain storm optimization for power electronic circuit optimization. 183-184
Track: search based software engineering
- Xin Cheng, Yuanyuan Huang, Xinye Cai, Ou Wei:
An adaptive memetic agorithm based on multiobjecitve optimization for software next release problem. 185-186 - Mohamed Wiem Mkaouer, Marouane Kessentini, Slim Bechikh, Mel Ó Cinnéide, Kalyanmoy Deb:
Software refactoring under uncertainty: a robust multi-objective approach. 187-188 - Zhilei Ren, He Jiang, Jifeng Xuan, Shuwei Zhang, Zhongxuan Luo:
Learning from evolved next release problem instances. 189-190
Track: self-* search
- Arthur Ervin Avramiea, Giorgos Karafotias, A. E. Eiben:
Fate agent evolutionary algorithms with self-adaptive mutation. 191-192 - Stephanus Daniel Handoko, Duc Thien Nguyen, Zhi Yuan, Hoong Chuin Lau:
Reinforcement learning for adaptive operator selection in memetic search applied to quadratic assignment problem. 193-194 - Matthew A. Martin, Daniel R. Tauritz:
Multi-sample evolution of robust black-box search algorithms. 195-196 - Mustafa Misir, Stephanus Daniel Handoko, Hoong Chuin Lau:
Building algorithm portfolios for memetic algorithms. 197-198 - Luís F. Simões, A. E. Eiben:
On the locality of neural meta-representations. 199-200
Track: theory
- Maxim Buzdalov, Arina Buzdalova:
Onemax helps optimizing XdivK: : theoretical runtime analysis for RLS and EA+RL. 201-202 - Narine Manukyan, Margaret J. Eppstein, Jeffrey S. Buzas:
NM landscapes: beyond NK. 203-204
Introductory tutorials
- Erik D. Goodman:
Introduction to genetic algorithms. 205-226 - Una-May O'Reilly:
Genetic programming: a tutorial introduction. 227-250 - Thomas Bäck:
Introduction to evolution strategies. 251-280 - Kenneth A. De Jong:
Evolutionary computation: a unified approach. 281-296 - Dimo Brockhoff:
GECCO 2014 tutorial on evolutionary multiobjective optimization. 297-322 - Franz Rothlauf:
Representations for evolutionary algorithms. 323-344 - Mark Wineberg:
Statistical analysis for evolutionary computation: an introduction. 345-380 - Andries P. Engelbrecht:
Particle swarm optimization. 381-406 - Pier Luca Lanzi:
Learning classifier systems: a gentle introduction. 407-430 - Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms. 431-458 - Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of evolutionary algorithms: basic introduction. 459-486 - Risto Miikkulainen:
Evolving neural networks. 487-512
Advanced tutorials
- Nikolaus Hansen, Anne Auger:
Evolution strategies and CMA-ES (covariance matrix adaptation). 513-534 - Carlos Artemio Coello Coello:
Constraint-handling techniques used with evolutionary algorithms. 535-558 - L. Darrell Whitley:
Blind no more: constant time non-random improving moves and exponentially powerful recombination. 559-580 - Lee Spector:
Expressive genetic programming. 581-606 - Frank Neumann, Andrew M. Sutton:
Parameterized complexity analysis of evolutionary algorithms. 607-622