Genetic programming and emergence. Genetic Programming and Evolvable Machines, pp.63-73, 2014. ,
DOI : 10.1007/s10710-013-9196-7
URL : http://www.cs.mun.ca/~banzhaf/papers/GP_and_Emergence.pdf
The effect of extensive use of the mutation operator on generalization in genetic programming using sparse data sets, Parallel Problem Solving from Nature IV, Proceedings of the International Conference on Evolutionary Computation, pp.300-309, 1996. ,
DOI : 10.1007/3-540-61723-X_994
Semantically driven crossover in genetic programming, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), pp.111-116, 2008. ,
DOI : 10.1109/CEC.2008.4630784
URL : http://www.cs.kent.ac.uk/pubs/2008/2783/content.pdf
Semantically driven mutation in genetic programming, 2009 IEEE Congress on Evolutionary Computation, pp.1336-1342, 2009. ,
DOI : 10.1109/CEC.2009.4983099
URL : http://www.cs.kent.ac.uk/pubs/2009/2924/content.pdf
Using direct competition to select for competent controllers in evolutionary robotics. Fcm: The fuzzy c-means clustering algorithm, pp.2-3191, 1984. ,
Pattern Recognition and Machine Learning (Information Science and Statistics), 2006. ,
Linear Genetic Programming, 2010. ,
Random forests, Machine learning, pp.5-32, 2001. ,
Cambrian intelligence: the early history of the new AI, 1999. ,
Attribute bagging: improving accuracy of classifier ensembles by using random feature subsets, Pattern Recognition, vol.36, issue.6, pp.1291-1302, 2003. ,
DOI : 10.1016/S0031-3203(02)00121-8
Is increased diversity in genetic programming beneficial? An analysis of lineage selection, The 2003 Congress on Evolutionary Computation, 2003. CEC '03., 2004. ,
DOI : 10.1109/CEC.2003.1299834
A comparison of the generalization ability of different genetic programming frameworks, IEEE Congress on Evolutionary Computation, pp.1-8, 2010. ,
DOI : 10.1109/CEC.2010.5585925
A Quantitative Study of Learning and Generalization in Genetic Programming, Lecture Notes in Computer Science, vol.13, issue.2, pp.25-36, 2011. ,
DOI : 10.1109/TEVC.2008.926486
Prediction of energy performance of residential buildings: A genetic programming approach, Energy and Buildings, vol.102, pp.67-74, 2015. ,
DOI : 10.1016/j.enbuild.2015.05.013
Semantic Search-Based Genetic Programming and the Effect of Intron Deletion, IEEE Transactions on Cybernetics, vol.44, issue.1, pp.103-113, 2014. ,
DOI : 10.1109/TSMCC.2013.2247754
Novelty-based restarts for evolution strategies, 2011 IEEE Congress of Evolutionary Computation (CEC), pp.158-163, 2011. ,
DOI : 10.1109/CEC.2011.5949613
URL : http://www.idsia.ch/~giuse/papers/cuccu11cec.pdf
Novelty-based restarts for evolution strategies The only challenging problems are deceptive: global search by solving order-1 hyperplanes. Number no, IEEE Congress on Evolutionary Computation, pp.158-163, 1991. ,
The Blind Watchmaker: Why the evidence of evolution reveals a universe without design, 1986. ,
Climbing Mount Improbable, 1996. ,
Multi-objective fast messy genetic algorithm solving deception problems, Congress on Evolutionary Computation, p.23, 2004. ,
DOI : 10.1109/cec.2004.1331074
URL : http://www.lania.mx/~ccoello/EMOO/day05.pdf.gz
Sufficient conditions for deceptive and easy binary functions, Annals of Mathematics and Artificial Intelligence, vol.2, issue.2, pp.385-408, 1994. ,
DOI : 10.1080/09528139008953717
Analyzing Deception in Trap Functions, Foundations of Genetic Algorithms, pp.93-108, 1993. ,
DOI : 10.1016/B978-0-08-094832-4.50012-X
Foundations in Grammatical Evolution for Dynamic Environments, of Studies in Computational Intelligence, 2009. ,
DOI : 10.1007/978-3-642-00314-1
URL : https://link.springer.com/content/pdf/bfm%3A978-3-642-00314-1%2F1.pdf
A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms, Swarm and Evolutionary Computation, vol.1, issue.1, pp.3-18, 2011. ,
DOI : 10.1016/j.swevo.2011.02.002
Binary genetic encoding for the synthesis of mixed-mode circuit topologies, Circuits, Systems, and Signal Processing, issue.3, pp.31849-863, 2011. ,
Pattern Classification, 2000. ,
A Real-Time Evolutionary Object Recognition System, Genetic Programming, pp.268-279, 2009. ,
DOI : 10.1109/ISWC.2002.1167222
URL : http://www.ra.cs.uni-tuebingen.de/mitarb/ebner/research/publications/uniTu2/EvoCV.pdf
Selection of the optimal sizes of analog integrated circuits by fuzzy sets intersection, Latin America Transactions IEEE (Revista IEEE America Latina), issue.6, pp.121005-1011, 2014. ,
Benchmarking the generalization capabilities of a compiling genetic programming system using sparse data sets, Proceedings of the 1st Annual Conference on Genetic Programming, pp.72-80, 1996. ,
Dynamic training subset selection for supervised learning in Genetic Programming, Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature, PPSN III, pp.312-321, 1994. ,
DOI : 10.1007/3-540-58484-6_275
Constituent Grammatical Evolution, 2012. ,
jge -a java implementation of grammatical evolution Grammatical evolution and the santa fe trail problem, 10th WSEAS International Conference on Systems International Conference on Evolutionary Computation (ICEC), pp.534-869, 2006. ,
Computer-aided design of analog and mixed-signal integrated circuits, Proceedings of the IEEE, pp.1825-1854, 2000. ,
DOI : 10.1109/5.899053
Simple genetic algorithms and the minimal, deceptive problem, Genetic algorithms and simulated annealing, pp.74-88, 1987. ,
Genetic Algorithms in Search, Optimization, and Machine Learning, 1989. ,
Devising Effective Novelty Search Algorithms, Proceedings of the 2015 on Genetic and Evolutionary Computation Conference, GECCO '15, pp.943-950, 2015. ,
DOI : 10.1016/B978-0-08-050684-5.50017-3
Progressive Minimal Criteria Novelty Search, Advances in Artificial Intelligence ? IBERAMIA 2012, pp.281-290, 2012. ,
DOI : 10.1007/978-3-642-34654-5_29
Evolution of swarm robotics systems with novelty search, Swarm Intelligence, vol.40, issue.2???3, pp.115-144, 2013. ,
DOI : 10.1016/S0921-8890(02)00232-4
URL : http://arxiv.org/pdf/1304.3362
Experiments on controlling overfitting in genetic programming, 15th Portuguese Conference on Artificial Intelligence, 2011. ,
Balancing Learning and Overfitting in Genetic Programming with Interleaved Sampling of Training Data, 15th Portuguese Conference on Artificial Intelligence. EPIA 2011. bibliography Gonçalves, Genetic Programming, pp.73-84, 2011. ,
DOI : 10.1007/978-3-642-37207-0_7
On the Generalization Ability of Geometric Semantic Genetic Programming, 18th European Conference on Genetic Programming, 2015. ,
DOI : 10.1007/978-3-319-16501-1_4
Random Sampling Technique for Overfitting Control in Genetic Programming, Genetic Programming, pp.218-229, 2012. ,
DOI : 10.1007/978-3-642-29139-5_19
Deception considered harmful, Foundations of Genetic Algorithms 2, pp.75-91, 1993. ,
DOI : 10.21236/ADA294072
URL : ftp://ftp.aic.nrl.navy.mil/pub/papers/1992/AIC-92-014.ps.Z
Practical genetic algorithms, J. Wiley, 2004. ,
DOI : 10.1002/0471671746
Visual learning of texture descriptors for facial expression recognition in thermal imagery, Computer Vision and Image Understanding, vol.106, issue.2-3, pp.258-269, 2007. ,
DOI : 10.1016/j.cviu.2006.08.012
The random subspace method for constructing decision forests. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.20, issue.8, pp.832-844, 1998. ,
Adaptation in Natural and Artificial Systems, 1975. ,
Genetic algorithms, problem difficulty , and the modality of fitness landscapes, FOGA'95, 1995. ,
Target detection in SAR imagery by genetic programming, Advances in Engineering Software, vol.30, issue.5, pp.303-311, 1999. ,
DOI : 10.1016/S0965-9978(98)00093-3
A Multi-dimensional Genetic Programming Approach for Multi-class Classification Problems, Genetic Programming Multi-dimensional Genetic Programming Approach for Multi-class Classification Problems, pp.48-60, 2014. ,
DOI : 10.1007/978-3-662-44303-3_5
Data clustering: 50 years beyond k-means, Pattern Recognition Letters, issue.8, pp.31651-666, 2010. ,
DOI : 10.1007/978-3-540-87479-9_3
A Description of Holland's Royal Road Function, Evolutionary Computation, vol.7, issue.4, pp.409-415, 1994. ,
DOI : 10.1162/evco.1994.2.4.409
Fitness distance correlation as a measure of problem difficulty for genetic algorithms, Proceedings of the Sixth International Conference on Genetic Algorithms, pp.184-192, 1995. ,
Reinforcement learning: A survey, Journal of Artificial Intelligence Research, vol.4, pp.237-285, 1996. ,
Critical factors in the performance of novelty search, Proceedings of the 13th annual conference on Genetic and evolutionary computation, GECCO '11, pp.965-972, 2011. ,
DOI : 10.1145/2001576.2001708
Promoting Creative Design in Interactive Evolutionary Computation, IEEE Transactions on Evolutionary Computation, vol.16, issue.4, pp.523-536, 2012. ,
DOI : 10.1109/TEVC.2011.2166764
URL : http://www.csse.monash.edu.au/%7Ecema/evoeco/kowaliw_evoeco_tec2011.pdf
Human-competitive results produced by genetic programming, Genetic Programming and Evolvable Machines, vol.2, issue.3, pp.251-284, 2010. ,
DOI : 10.1007/3-540-61093-6_5
Genetic programming as a means for programming computers by natural selection, Statistics and Computing, vol.4, issue.2, 1992. ,
DOI : 10.1007/BF00175355
Genetic Programming: On the Programming of Computers by Means of Natural Selection. Complex adaptive systems, 1992. ,
Genetic Programming Theory and Practice II, chapter, Automated Design of Industrial-Strength Analog Circuits by Means of Genetic Programming, pp.121-142, 2005. ,
Automatic creation of human-competitive programs and controllers by means of genetic programming, Genetic Programming and Evolvable Machines, vol.1, issue.1/2, pp.121-164, 2000. ,
DOI : 10.1023/A:1010076532029
Routine high-return human-competitive automated problem-solving by means of genetic programming, Information Sciences, vol.178, issue.23, pp.1784434-4452, 2008. ,
DOI : 10.1016/j.ins.2008.07.028
Genetic programming-based construction of features for machine learning and knowledge discovery tasks, Genetic Programming and Evolvable Machines, vol.3, issue.4, pp.329-343, 2002. ,
DOI : 10.1023/A:1020984725014
Visual Learning by Coevolutionary Feature Synthesis, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.35, issue.3, pp.409-425, 2005. ,
DOI : 10.1109/TSMCB.2005.846644
URL : http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.654.8302&rep=rep1&type=pdf
Locally geometric semantic crossover: a study on the roles of semantics and homology in recombination operators, Genetic Programming and Evolvable Machines, vol.3, issue.3, pp.31-63, 2013. ,
DOI : 10.1007/978-3-642-14156-0
An evaluation of evolutionary generalisation in genetic programming, Artificial Intelligence Review, vol.18, issue.1, pp.3-14, 2002. ,
DOI : 10.1023/A:1016379201230
Genetic programming and evolutionary generalization, IEEE Transactions on Evolutionary Computation, vol.6, issue.5, pp.431-442, 2002. ,
DOI : 10.1109/TEVC.2002.805038
Foundations of Genetic Programming, 2001. ,
DOI : 10.1007/978-3-662-04726-2
Fitness Causes Bloat, Proceedings of the Second On-line World Conference on Soft Computing in Engineering Design and Manufacturing, pp.13-22, 1997. ,
DOI : 10.1007/978-1-4471-0427-8_2
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation, 2001. ,
Exploiting open-endedness to solve problems through the search for novelty, Proceedings of the Eleventh International Conference on Artificial Life, 2008. ,
Efficiently evolving programs through the search for novelty, Proceedings of the 12th annual conference on Genetic and evolutionary computation, GECCO '10, pp.837-844, 2010. ,
DOI : 10.1145/1830483.1830638
Efficiently evolving programs through the search for novelty, Proceedings of the 12th annual conference on Genetic and evolutionary computation, GECCO '10, pp.837-844, 2010. ,
DOI : 10.1145/1830483.1830638
Revising the evolutionary computation abstraction, Proceedings of the 12th annual conference on Genetic and evolutionary computation, GECCO '10, pp.103-110, 2010. ,
DOI : 10.1145/1830483.1830503
Abandoning Objectives: Evolution Through the Search for Novelty Alone, Evolutionary Computation, vol.7, issue.3, pp.189-223, 2011. ,
DOI : 10.1016/0165-6074(93)90215-7
URL : http://www.mitpressjournals.org/userimages/ContentEditor/1164817256746/lib_rec_form.pdf
Evolving a diversity of virtual creatures through novelty search and local competition, Proceedings of the 13th annual conference on Genetic and evolutionary computation, GECCO '11, pp.211-218, 2011. ,
DOI : 10.1145/2001576.2001606
Behavioural biologists do not agree on what constitutes behaviour, Animal Behaviour, vol.78, issue.1, pp.103-110, 2009. ,
DOI : 10.1016/j.anbehav.2009.03.018
URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2760923/pdf
Essentials of Metaheuristics. Lulu, second edition, 2013. ,
Tarpeian Bloat Control and Generalization Accuracy, Proceedings of the 8th European Conference on Genetic Programming, pp.203-214, 2005. ,
DOI : 10.1007/978-3-540-31989-4_18
Classification of analog synthesis tools based on their architecture selection mechanisms, Integration, the VLSI Journal, vol.41, issue.2, pp.238-252, 2008. ,
DOI : 10.1016/j.vlsi.2007.06.001
Searching for novel regression functions, 2013 IEEE Congress on Evolutionary Computation, pp.16-23, 2013. ,
DOI : 10.1109/CEC.2013.6557548
A comparison of fitness-case sampling methods for symbolic regression with genetic programming Genetic Algorithms for VLSI Design, Layout & Test Automation, of Advances in Intelligent Systems and Computing, pp.201-212, 1999. ,
A finegrained view of phenotypes and locality in genetic programming, Genetic Programming Theory and Practice IX, Genetic and Evolutionary Computation, pp.57-76, 2011. ,
Genetic programming needs better benchmarks, Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference, GECCO '12, pp.791-798, 2012. ,
DOI : 10.1145/2330163.2330273
Deceptive and other functions of unitation as bayesian networks, 1998. ,
Geometric Semantic Genetic Programming, Proceedings of the 12th international conference on Parallel Problem Solving from Nature -Volume Part I, PPSN'12, pp.21-31, 2012. ,
DOI : 10.1007/978-3-642-32937-1_3
Novelty-Based Multiobjectivization, New Horizons in Evolutionary Robotics, pp.139-154, 2011. ,
DOI : 10.1007/978-3-642-18272-3_10
URL : https://hal.archives-ouvertes.fr/hal-01300711
Encouraging Behavioral Diversity in Evolutionary Robotics: An Empirical Study, Evolutionary Computation, vol.341, issue.1, pp.91-133, 2012. ,
DOI : 10.1016/0020-0190(92)90136-J
URL : https://hal.archives-ouvertes.fr/hal-00687609
M3GP ??? Multiclass Classification with GP, Genetic Programming, pp.78-91, 2015. ,
DOI : 10.1007/978-3-319-16501-1_7
Improving Generalization Ability of Genetic Programming: Comparative Study, Journal of Bioinformatics and Intelligent Control, vol.2, issue.4, 2013. ,
DOI : 10.1166/jbic.2013.1063
URL : http://arxiv.org/abs/1304.3779
Novelty Search for the Synthesis of Current Followers, Computaci??n y Sistemas, vol.20, issue.4, 2016. ,
DOI : 10.13053/cys-20-4-2502
Disparity Map Estimation by Combining Cost Volume Measures Using Genetic Programming, EVOLVE -A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II, volume 175 of Advances in Intelligent Systems and Computing, pp.71-86, 2013. ,
DOI : 10.1007/978-3-642-31519-0_5
Searching for novel clustering programs, Proceeding of the fifteenth annual conference on Genetic and evolutionary computation conference, GECCO '13, p.13, 2013. ,
DOI : 10.1145/2463372.2463505
URL : http://eplex.cs.ucf.edu/noveltysearch/userspage/GECCO-2013-Trujillo.pdf
DiseñandoDise?Diseñando problemas sintéticos de clasificací on con superficie de aptitud deceptiva, X Congreso Español de Metaheurísticas, 2015. ,
Evolving genetic programming classifiers with novelty search, Information Sciences, vol.369, 2016. ,
DOI : 10.1016/j.ins.2016.06.044
URL : https://hal.archives-ouvertes.fr/hal-01111234
Searching for Novel Classifiers, Proceedings from the 16th European Conference on Genetic Programming, pp.145-156, 2013. ,
DOI : 10.1007/978-3-642-37207-0_13
URL : http://eplex.cs.ucf.edu/noveltysearch/userspage/naredo_EvoStar.pdf
The training set and generalization in grammatical evolution for autonomous agent navigation, Soft Computing, vol.64, issue.3???4, pp.1-18, 2016. ,
DOI : 10.1145/1830483.1830643
Fitness functions in evolutionary robotics: A survey and analysis, Robotics and Autonomous Systems, vol.57, issue.4, pp.345-370, 2009. ,
DOI : 10.1016/j.robot.2008.09.009
An Investigation of Fitness Sharing with Semantic and Syntactic Distance Metrics, Proceedings of the 15th European Conference on Genetic Programming, pp.109-120, 2012. ,
DOI : 10.1007/978-3-642-29139-5_10
Mechanisms to avoid the premature convergence of genetic algorithms. Petroleum -Gas University of Ploiesti Bulletin, Mathematics -Informatics -Physics Series, vol.61, issue.1, pp.87-96, 2009. ,
Evolutionary Robotics, 2000. ,
DOI : 10.1016/S0921-8890(96)00034-6
Avida: A Software Platform for Research in Computational Evolutionary Biology, Artificial Life, vol.75, issue.2, pp.191-229, 2004. ,
DOI : 10.1038/nature01151
Evolutionary-computer-assisted design of image operators that detect interest points using genetic programming, Image and Vision Computing, vol.29, issue.7, pp.484-498, 2011. ,
DOI : 10.1016/j.imavis.2011.03.004
Grammatical evolution, IEEE Transactions on Evolutionary Computation, vol.5, issue.4, pp.349-358, 2001. ,
DOI : 10.1109/4235.942529
Open issues in genetic programming, Genetic Programming and Evolvable Machines, vol.11, issue.34, pp.339-363, 2010. ,
A survey of optimization by building and using probabilistic models, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334), pp.5-20, 2002. ,
DOI : 10.1109/ACC.2000.879173
Learning invariant region descriptor operators with genetic programming and the f-measure, 19th International Conference on Pattern Recognition, pp.1-4, 2008. ,
Evolutionary learning of local descriptor operators for object recognition, Proceedings of the 11th Annual conference on Genetic and evolutionary computation, GECCO '09, pp.1051-1058, 2009. ,
DOI : 10.1145/1569901.1570043
Cartesian Genetic Programming. Natural Computing Series, 2000. ,
Genetic Programming for feature detection and image segmentation, AISB Workshop Evolutionary Computing, pp.110-125, 1996. ,
DOI : 10.1007/BFb0032777
URL : http://www.cs.bham.ac.uk/~rmp/papers/Poli-AISB-1996.ps.gz
A field guide to genetic programming. Published via http, 2008. ,
A Field Guide to Genetic Programming, 2008. ,
A Genetic Programming Approach to Estimate Vegetation Cover in the Context of Soil Erosion Assessment, Photogrammetric Engineering & Remote Sensing, vol.77, issue.4, pp.363-376, 2011. ,
DOI : 10.14358/PERS.77.4.363
Deception, blindness and disorientation in particle swarm optimization applied to noisy problems, Swarm Intelligence, vol.17, issue.6, pp.247-273, 2014. ,
DOI : 10.1007/s00500-013-1015-9
Examining the role of local optima and schema processing in genetic search, 1999. ,
Design of Analog CMOS Integrated Circuits Santa fe trail hazards, 7th International Conference on Artificial Evolution, pp.1-12, 2001. ,
The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music. Natural Computing Series, 2007. ,
DOI : 10.1007/978-3-540-72877-1
Generality versus size in genetic programming, Genetic Programming 1996: Proceedings of the First Annual Conference, pp.381-387, 1996. ,
Hierarchical Modeling, Optimization, and Synthesis for System-Level Analog and RF Designs, Proceedings of the IEEE, pp.640-669, 2007. ,
DOI : 10.1109/JPROC.2006.889371
Spurious Correlations and Premature Convergence in Genetic Algorithms, FOGA'90, pp.102-112, 1990. ,
DOI : 10.1016/B978-0-08-050684-5.50010-0
Evolving Generalised Maze Solvers, Applications of Evolutionary Computation, pp.783-794, 2015. ,
DOI : 10.1007/978-3-319-16549-3_63
Gplab?a genetic programming toolbox for matlab, Proceedings of the Nordic MAT- LAB conference, pp.273-278, 2003. ,
Dynamic limits for bloat control in genetic programming and a review of past and current bloat theories, Genetic Programming and Evolvable Machines, vol.3, issue.1, pp.141-179, 2009. ,
DOI : 10.1007/s10710-008-9075-9
Texture Segmentation by Genetic Programming, Evolutionary Computation, vol.1999, issue.4, pp.461-481, 2008. ,
DOI : 10.1142/S0218213007003576
URL : http://www.mitpressjournals.org/userimages/ContentEditor/1164817256746/lib_rec_form.pdf
Assessment of problem modality by differential performance of lexicase selection in genetic programming: A preliminary report, Proceedings of the 14th Annual Conference Companion on Genetic and Evolutionary Computation, pp.401-408, 2012. ,
Genetic programming and autoconstructive evolution with the push programming language, Genetic Programming and Evolvable Machines, pp.7-40, 2002. ,
MicroGP???An Evolutionary Assembly Program Generator, Genetic Programming and Evolvable Machines, vol.30, issue.4, pp.247-263, 2005. ,
DOI : 10.1147/rd.33.0282
Efficient Evolution of Neural Networks Through Complexification, 2004. ,
Compositional pattern producing networks: A novel abstraction of development, Genetic Programming and Evolvable Machines, vol.1143, issue.2, pp.131-162, 2007. ,
DOI : 10.1007/978-1-4613-8476-2
Why Greatness Cannot Be Planned: The Myth of the Objective, 2015. ,
DOI : 10.1007/978-3-319-15524-1
Fingerprint Classification Based on Learned Features, IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), vol.35, issue.3, pp.287-300, 2005. ,
DOI : 10.1109/TSMCC.2005.848167
URL : http://vislab.ucr.edu/PUBLICATIONS/pubs/Journal+and+Conference+Papers/after10-1-1997/Journals/2005/Fingerprint+Classification+Based05.pdf
Pattern Recognition, Fourth Edition, 2008. ,
Introduction to Pattern Recognition: A Matlab Approach, 2010. ,
Success in Evolutionary Computation, chapter Evolutionary Electronics: Automatic bibliography Synthesis of Analog Circuits by GAs, pp.165-187, 2008. ,
Automatic synthesis of electronic circuits using genetic algorithms, pp.217-229, 2007. ,
Applications of evolutionary algorithms in the design automation of analog integrated circuits, Journal of Applied Sciences, vol.10, pp.1859-1872, 2010. ,
The estimation of hölderian regularity using genetic programming, GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation, pp.861-868, 2010. ,
Genetic Programming: 17th European Conference Revised Selected Papers, chapter NEAT, There's No Bloat, pp.174-185, 2014. ,
Preliminary Study of Bloat in Genetic Programming with Behavior-Based Search, EVOLVE -A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV of Advances in Intelligent Systems and Computing, pp.293-305, 2013. ,
DOI : 10.1007/978-3-319-01128-8_19
Behaviorbased speciation for evolutionary robotics, GECCO, pp.297-298, 2008. ,
Discovering Several Robot Behaviors through Speciation, Proceedings of the 2008 conference on Applications of evolutionary computing, Evo'08, pp.164-174, 2008. ,
DOI : 10.1007/978-3-540-78761-7_17
URL : http://cienciascomp.cicese.mx/evovision/olague_EvoIASP08a.pdf
Speciation in Behavioral Space for Evolutionary Robotics, Journal of Intelligent & Robotic Systems, vol.29, issue.6, pp.3-4323, 2011. ,
DOI : 10.1109/TPAMI.2007.1078
URL : https://hal.archives-ouvertes.fr/hal-00642312
Multiobjective design of operators that detect points of interest in images, Proceedings of the 10th annual conference on Genetic and evolutionary computation, GECCO '08, pp.1299-1306, 2008. ,
DOI : 10.1145/1389095.1389344
An Empirical Study of Functional Complexity as an Indicator of Overfitting in Genetic Programming, Lecture Notes in Computer Science, vol.13, issue.2, pp.262-273, 2011. ,
DOI : 10.1109/TEVC.2008.926486
URL : https://hal.archives-ouvertes.fr/hal-00642530
A behavior-based analysis of modal problems, Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion, GECCO '13 Companion, pp.1047-1054, 2013. ,
DOI : 10.1145/2464576.2482682
Improving Grammatical Evolution in Santa Fe Trail using Novelty Search, Advances in Artificial Life, ECAL 2013, pp.917-924, 2013. ,
DOI : 10.7551/978-0-262-31709-2-ch137
URL : http://mitpress.mit.edu/sites/default/files/titles/content/ecal13/978-0-262-31709-2-ch137.pdf
Generalization in Maze Navigation Using Grammatical Evolution and Novelty Search, Theory and Practice of Natural Computing Theory and Practice of Natural Computing, pp.35-46, 2014. ,
DOI : 10.1007/978-3-319-13749-0_4
Improving the Generalisation Ability of Genetic Programming with Semantic Similarity based Crossover, Proceedings of the 13th European Conference on Genetic Programming, EuroGP'10, pp.184-195, 2010. ,
DOI : 10.1007/978-3-642-12148-7_16
Semantically-based crossover in genetic programming: application to real-valued symbolic regression, Genetic Programming and Evolvable Machines, vol.5, issue.2, pp.91-119, 2011. ,
DOI : 10.1162/evco.1997.5.2.123
Semantically-based crossover in genetic programming: application to real-valued symbolic regression, Genetic Programming and Evolvable Machines, vol.5, issue.2, pp.91-119, 2011. ,
DOI : 10.1162/evco.1997.5.2.123
Measuring bloat, overfitting and functional complexity in genetic programming, Proceedings of the 12th annual conference on Genetic and evolutionary computation, GECCO '10, pp.877-884, 2010. ,
DOI : 10.1145/1830483.1830643
Novelty search creates robots with general skills for exploration, Proceedings of the 2014 conference on Genetic and evolutionary computation, GECCO '14, pp.737-744, 2014. ,
DOI : 10.1145/2576768.2598225
Evolutionary Electronics: Automatic Design of Electronic Circuits and Systems by Genetic Algorithms, p.1, 2001. ,
Correlated and uncorrelated fitness landscapes and how to tell the difference, Biological Cybernetics, vol.1, issue.5, pp.325-336, 1990. ,
DOI : 10.1051/jphys:019850046080127700
Frequency Fitness Assignment, IEEE Transactions on Evolutionary Computation, vol.18, issue.2, pp.226-243, 2014. ,
DOI : 10.1109/TEVC.2013.2251885
URL : http://www.cs.bham.ac.uk/~xin/papers/tevc2013FFA.pdf
Fundamental Principles of Deception in Genetic Search, Foundations of Genetic Algorithms, pp.221-241, 1991. ,
DOI : 10.1016/B978-0-08-050684-5.50017-3
Netlogo, Evanston, IL: Center for Connected Learning and Computer-Based Modeling, pp.9-2016, 1999. ,
Exploring promising stepping stones by combining novelty search with interactive evolution, 1207. ,
Adaptive group mutation for tackling deception in genetic search, WSEAS Transactions on Systems, vol.3, issue.1, pp.107-112, 2004. ,
Using Gaussian distribution to construct fitness functions in genetic programming for multiclass object classification, Pattern Recognition Letters, vol.27, issue.11, pp.1266-1274, 2006. ,
DOI : 10.1016/j.patrec.2005.07.024