Darwin or Lamarck? Future Challenges in Evolutionary Algorithms for Knowledge Discovery and Data Mining
暂无分享,去创建一个
Andreas Holzinger | Vasile Palade | Katharina Holzinger | Raul Rabadan | R. Rabadán | V. Palade | Andreas Holzinger | K. Holzinger
[1] Anne Auger,et al. Theory of Evolution Strategies: A New Perspective , 2011, Theory of Randomized Search Heuristics.
[2] Václav Snásel,et al. A Modified Invasive Weed Optimization Algorithm for training of feed- forward Neural Networks , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.
[3] Hong Zhu,et al. Invasive Weed Optimization Algorithm for Optimizating the Parameters of Mixed Kernel Twin Support Vector Machines , 2013, J. Comput..
[4] John R. Koza,et al. Genetic programming as a means for programming computers by natural selection , 1994 .
[5] Larry Bull,et al. On the Baldwin Effect , 1999, Artificial Life.
[6] Peter Pirolli,et al. Information Foraging , 2009, Encyclopedia of Database Systems.
[7] Christian Blum,et al. Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.
[8] Yuhui Shi,et al. Particle swarm optimization: developments, applications and resources , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).
[9] Hossein Nezamabadi-pour,et al. BGSA: binary gravitational search algorithm , 2010, Natural Computing.
[10] A. Bennett. The Origin of Species by means of Natural Selection; or the Preservation of Favoured Races in the Struggle for Life , 1872, Nature.
[11] Andreas Holzinger,et al. Darwin, Lamarck, or Baldwin: Applying Evolutionary Algorithms to Machine Learning Techniques , 2014, 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).
[12] Soojin V Yi,et al. Epigenetics and evolution. , 2014, Integrative and comparative biology.
[13] Russell C. Eberhart,et al. A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.
[14] Marco Dorigo,et al. Distributed Optimization by Ant Colonies , 1992 .
[15] Thomas Bäck,et al. A Survey of Evolution Strategies , 1991, ICGA.
[16] Trevor Cohen,et al. Discovery by scent: Discovery browsing system based on the Information Foraging Theory , 2012, 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops.
[17] Fernando Niño,et al. Recent Advances in Artificial Immune Systems: Models and Applications , 2011, Appl. Soft Comput..
[18] Kevin M. Passino,et al. Biomimicry of bacterial foraging for distributed optimization and control , 2002 .
[19] Ronen Feldman,et al. The Data Mining and Knowledge Discovery Handbook , 2005 .
[20] E. Jablonka,et al. Epigenetic Inheritance and Evolution: The Lamarckian Dimension , 1995 .
[21] Alex Alves Freitas,et al. Data mining with an ant colony optimization algorithm , 2002, IEEE Trans. Evol. Comput..
[22] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[23] Jason H. Moore,et al. Genetic programming neural networks: A powerful bioinformatics tool for human genetics , 2007, Appl. Soft Comput..
[24] John H. Holland,et al. Outline for a Logical Theory of Adaptive Systems , 1962, JACM.
[25] David E. Goldberg,et al. Genetic algorithms and Machine Learning , 1988, Machine Learning.
[26] Bart Baesens,et al. Editorial survey: swarm intelligence for data mining , 2010, Machine Learning.
[27] Dong Hwa Kim,et al. A hybrid genetic algorithm and bacterial foraging approach for global optimization , 2007, Inf. Sci..
[28] Keith L. Downing,et al. Introduction to Evolutionary Algorithms , 2006 .
[29] S Forrest,et al. Genetic algorithms , 1996, CSUR.
[30] Muhammad Khurram Khan,et al. An effective memetic differential evolution algorithm based on chaotic local search , 2011, Inf. Sci..
[31] Hari Balakrishnan,et al. TCP ex machina: computer-generated congestion control , 2013, SIGCOMM.
[32] D. Penny,et al. Branch and bound algorithms to determine minimal evolutionary trees , 1982 .
[33] W. Fitch,et al. Construction of phylogenetic trees. , 1967, Science.
[34] Andrew Lewis,et al. Grey Wolf Optimizer , 2014, Adv. Eng. Softw..
[35] Lothar Thiele,et al. Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..
[36] Alex Alves Freitas,et al. Discovering New Rule Induction Algorithms with Grammar-based Genetic Programming , 2008, Soft Computing for Knowledge Discovery and Data Mining.
[37] Jiming Liu,et al. Characterizing Web usage regularities with information foraging agents , 2004, IEEE Transactions on Knowledge and Data Engineering.
[38] Hans-Paul Schwefel,et al. Evolution strategies – A comprehensive introduction , 2002, Natural Computing.
[39] Mitsuo Gen,et al. Genetic algorithms and engineering optimization , 1999 .
[40] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[41] Irving M. Klotz,et al. Symposia of the Society for Experimental Biology , 1952, The Yale Journal of Biology and Medicine.
[42] Francesco Pappalardo,et al. Discovery of cancer vaccination protocols with a genetic algorithm driving an agent based simulator , 2006, BMC Bioinformatics.
[43] Michael Affenzeller,et al. Music Segmentation With Genetic Algorithms , 2009, 2009 20th International Workshop on Database and Expert Systems Application.
[44] Alan S. Perelson,et al. The immune system, adaptation, and machine learning , 1986 .
[45] Jonathan Timmis,et al. Artificial immune systems as a novel soft computing paradigm , 2003, Soft Comput..
[46] Frank Hoffmeister,et al. Scalable Parallelism by Evolutionary Algorithms , 1991 .
[47] George E. P. Box,et al. Evolutionary Operation: a Method for Increasing Industrial Productivity , 1957 .
[48] Marco Dorigo,et al. Ant colony optimization theory: A survey , 2005, Theor. Comput. Sci..
[49] Praveen Ranjan Srivastava,et al. Code coverage using intelligent water drop (IWD) , 2012, Int. J. Bio Inspired Comput..
[50] Caro Lucas,et al. A novel numerical optimization algorithm inspired from weed colonization , 2006, Ecol. Informatics.
[51] Frank Klawonn,et al. Künstliche neuronale Netze , 2011 .
[52] Haibing Li,et al. Applying Ant Colony Optimization to configuring stacking ensembles for data mining , 2014, Expert Syst. Appl..
[53] Lale Özbakir,et al. Bees algorithm for generalized assignment problem , 2010, Appl. Math. Comput..
[54] Hossein Nezamabadi-pour,et al. A discrete gravitational search algorithm for solving combinatorial optimization problems , 2014, Inf. Sci..
[55] Andreas Zell,et al. Evolution strategy with neighborhood attraction – a robust evolution strategy , 2001 .
[56] Anne Auger,et al. Theory of Randomized Search Heuristics: Foundations and Recent Developments , 2011, Theory of Randomized Search Heuristics.
[57] C. Waddington. Canalization of Development and the Inheritance of Acquired Characters , 1942, Nature.
[58] Wolfgang Banzhaf,et al. A comparison of linear genetic programming and neural networks in medical data mining , 2001, IEEE Trans. Evol. Comput..
[59] Russell C. Eberhart,et al. A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.
[60] Thomas Jansen,et al. Analyzing Evolutionary Algorithms: The Computer Science Perspective , 2012 .
[61] Marco Dorigo,et al. An Investigation of some Properties of an "Ant Algorithm" , 1992, PPSN.
[62] C.A. Coello Coello,et al. MOPSO: a proposal for multiple objective particle swarm optimization , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
[63] P. D. de Boer,et al. Advances in understanding E. coli cell fission. , 2010, Current opinion in microbiology.
[64] Liu Junlan,et al. Covering fuzzy S-rough sets model , 2011 .
[65] E. Bonabeau. Decisions 2.0: the power of collective intelligence , 2009 .
[66] Paula A. Kiberstis. All Eyes on Epigenetics , 2012 .
[67] Sukumar Mishra,et al. Transmission Loss Reduction Based on FACTS and Bacteria Foraging Algorithm , 2006, PPSN.
[68] Luca Maria Gambardella,et al. Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..
[69] L. Darrell Whitley,et al. An overview of evolutionary algorithms: practical issues and common pitfalls , 2001, Inf. Softw. Technol..
[70] Kwang Mong Sim,et al. Ant colony optimization for routing and load-balancing: survey and new directions , 2003, IEEE Trans. Syst. Man Cybern. Part A.
[71] N. Saitou,et al. The neighbor-joining method: a new method for reconstructing phylogenetic trees. , 1987, Molecular biology and evolution.
[72] Don Tapscott,et al. Grown Up Digital: How the Net Generation is Changing Your World , 2008 .
[73] Hamed Shah-Hosseini,et al. The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm , 2009, Int. J. Bio Inspired Comput..
[74] R. Lewontin. ‘The Selfish Gene’ , 1977, Nature.
[75] Adrian Bird,et al. Perceptions of epigenetics , 2007, Nature.
[76] Thomas Jansen,et al. Analyzing Evolutionary Algorithms , 2015, Natural Computing Series.
[77] Bob J. Wielinga,et al. The Mars crowdsourcing experiment: Is crowdsourcing in the form of a serious game applicable for annotation in a semantically-rich research domain? , 2011, 2011 16th International Conference on Computer Games (CGAMES).
[78] Hossein Nezamabadi-pour,et al. GSA: A Gravitational Search Algorithm , 2009, Inf. Sci..
[79] Hans-Georg Beyer,et al. The Theory of Evolution Strategies , 2001, Natural Computing Series.
[80] N. Ramaraj,et al. A novel hybrid feature selection via Symmetrical Uncertainty ranking based local memetic search algorithm , 2010, Knowl. Based Syst..
[81] Duc Truong Pham,et al. The Bees Algorithm: Modelling foraging behaviour to solve continuous optimization problems , 2009 .
[82] S. Jonjić,et al. Modulation of natural killer cell activity by viruses. , 2010, Current opinion in microbiology.
[83] Irfan Akca,et al. Application of Genetic Algorithms in Seismic Tomography , 2010 .
[84] Hsing-Chih Tsai,et al. Integrating the artificial bee colony and bees algorithm to face constrained optimization problems , 2014, Inf. Sci..
[85] John J. Grefenstette,et al. Optimization of Control Parameters for Genetic Algorithms , 1986, IEEE Transactions on Systems, Man, and Cybernetics.
[86] Alex Alves Freitas,et al. Evolving rule induction algorithms with multi-objective grammar-based genetic programming , 2009, Knowledge and Information Systems.
[87] Hisao Ishibuchi,et al. Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling , 2003, IEEE Trans. Evol. Comput..
[88] S. Pratt,et al. Information flow, opinion polling and collective intelligence in house-hunting social insects. , 2002, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[89] Peer Bork,et al. Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation , 2007, Bioinform..
[90] Colin R. Reeves,et al. Evolutionary computation: a unified approach , 2007, Genetic Programming and Evolvable Machines.
[91] A. E. Eiben,et al. Introduction to Evolutionary Computing , 2003, Natural Computing Series.
[92] Peter Pirolli,et al. Rational Analyses of Information Foraging on the Web , 2005, Cogn. Sci..
[93] R. W. Dobbins,et al. Computational intelligence PC tools , 1996 .
[94] Edmund K. Burke,et al. Parallel Problem Solving from Nature - PPSN IX: 9th International Conference, Reykjavik, Iceland, September 9-13, 2006, Proceedings , 2006, PPSN.
[95] Dervis Karaboga,et al. A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..
[96] David Coley,et al. Introduction to Genetic Algorithms for Scientists and Engineers , 1999 .
[97] Francisco Herrera,et al. Memetic algorithms based on local search chains for large scale continuous optimisation problems: MA-SSW-Chains , 2011, Soft Comput..
[98] Andreas Holzinger,et al. Functional and genetic analysis of the colon cancer network , 2014, BMC Bioinformatics.
[99] Hamed Shah-Hosseini,et al. Problem solving by intelligent water drops , 2007, 2007 IEEE Congress on Evolutionary Computation.
[100] D. Pham,et al. THE BEES ALGORITHM, A NOVEL TOOL FOR COMPLEX OPTIMISATION PROBLEMS , 2006 .
[101] Kazuhiro Ohkura,et al. Robust Evolution Strategies , 1998, Applied Intelligence.
[102] Alex A. Freitas,et al. A survey of evolutionary algorithms for data mining and knowledge discovery , 2003 .
[103] Meng Hongyun. Artificial bee colony algorithm with chaotic differential evolution search , 2011 .
[104] Sreeram V Ramagopalan,et al. Is Lamarckian evolution relevant to medicine? , 2010, BMC Medical Genetics.
[105] Mauro Birattari,et al. Swarm Intelligence , 2012, Lecture Notes in Computer Science.
[106] Cheng-Chew Lim,et al. Optimizing system-on-chip verifications with multi-objective genetic evolutionary algorithms , 2013 .
[107] P. A. J. Boer,et al. Advances in understanding E. coli cell fission , 2010 .
[108] Giovanni Squillero,et al. The selfish gene algorithm: a new evolutionary optimization strategy , 1998, SAC '98.
[109] Thomas Stützle,et al. Ant colony optimization: artificial ants as a computational intelligence technique , 2006 .
[110] D. Meyer,et al. Supporting Online Material Materials and Methods Som Text Figs. S1 to S6 References Evidence for a Collective Intelligence Factor in the Performance of Human Groups , 2022 .
[111] Frank Klawonn,et al. Computational Intelligence: A Methodological Introduction , 2015, Texts in Computer Science.