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Gotowe bibliografie tematyczne / Evolutionary computation / Artykuły w czasopismach

Artykuły w czasopismach na temat „Evolutionary computation”

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Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 30 lipca 2024

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1

Foster, James A. "Evolutionary computation". Nature Reviews Genetics 2, nr 6 (czerwiec 2001): 428–36. http://dx.doi.org/10.1038/35076523.

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2

Jong, Kenneth De. "Evolutionary computation". Wiley Interdisciplinary Reviews: Computational Statistics 1, nr 1 (lipiec 2009): 52–56. http://dx.doi.org/10.1002/wics.5.

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3

Kozlov, AP. "Biological Computation and Compatibility Search in the Possibility Space as the Mechanism of Complexity Increase During Progressive Evolution". Evolutionary Bioinformatics 18 (styczeń 2022): 117693432211106. http://dx.doi.org/10.1177/11769343221110654.

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The idea of computational processes, which take place in nature, for example, DNA computation, is discussed in the literature. DNA computation that is going on in the immunoglobulin locus of vertebrates shows how the computations in the biological possibility space could operate during evolution. We suggest that the origin of evolutionarily novel genes and genome evolution constitute the original intrinsic computation of the information about new structures in the space of unrealized biological possibilities. Due to DNA computation, the information about future structures is generated and stored in DNA as genetic information. In evolving ontogenies, search algorithms are necessary, which can search for information about evolutionary innovations and morphological novelties. We believe that such algorithms include stochastic gene expression, gene competition, and compatibility search at different levels of structural organization. We formulate the increase in complexity principle in terms of biological computation and hypothesize the possibility of in silico computing of future functions of evolutionarily novel genes.

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4

V, Shilpa, i Suma V. Shetty. "Design of Systolic Architecture Using Evolutionary Computation". International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (30.06.2018): 2815–20. http://dx.doi.org/10.31142/ijtsrd15776.

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5

Bush, Benjamin James, i Hiroki Sayama. "Hyperinteractive Evolutionary Computation". IEEE Transactions on Evolutionary Computation 15, nr 3 (czerwiec 2011): 424–33. http://dx.doi.org/10.1109/tevc.2010.2096539.

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6

Takagi, Hideyuki, i Hitoshi Iba. "Interactive evolutionary computation". New Generation Computing 23, nr 2 (czerwiec 2005): 113–14. http://dx.doi.org/10.1007/bf03037488.

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7

Ivkovic, Nikola, Domagoj Jakobovic i Marin Golub. "Measuring Performance of Optimization Algorithms in Evolutionary Computation". International Journal of Machine Learning and Computing 6, nr 3 (czerwiec 2016): 167–71. http://dx.doi.org/10.18178/ijmlc.2016.6.3.593.

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8

Brunello, Andrea, Enrico Marzano, Angelo Montanari i Guido Sciavicco. "Decision Tree Pruning via Multi-Objective Evolutionary Computation". International Journal of Machine Learning and Computing 7, nr 6 (grudzień 2017): 167–75. http://dx.doi.org/10.18178/ijmlc.2017.7.6.641.

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9

TAMAKI, Hisashi. "Evolutionary Computation and Optimization". Journal of Japan Society for Fuzzy Theory and Systems 10, nr 4 (1998): 593–601. http://dx.doi.org/10.3156/jfuzzy.10.4_13.

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10

Yasuda, Keiichiro. "Evolutionary Computation and Metaheuristics". IEEJ Transactions on Electronics, Information and Systems 122, nr 3 (2002): 320–23. http://dx.doi.org/10.1541/ieejeiss1987.122.3_320.

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11

López-ibáñez, Manuel, Juergen Branke i Luís Paquete. "Reproducibility in Evolutionary Computation". ACM Transactions on Evolutionary Learning and Optimization 1, nr 4 (31.12.2021): 1–21. http://dx.doi.org/10.1145/3466624.

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Experimental studies are prevalent in Evolutionary Computation ( EC ), and concerns about the reproducibility and replicability of such studies have increased in recent times, reflecting similar concerns in other scientific fields. In this article, we discuss, within the context of EC, the different types of reproducibility and suggest a classification that refines the badge system of the Association of Computing Machinery ( ACM ) adopted by ACM Transactions on Evolutionary Learning and Optimization ( TELO ). We identify cultural and technical obstacles to reproducibility in the EC field. Finally, we provide guidelines and suggest tools that may help to overcome some of these reproducibility obstacles.

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12

Lucas, S. M., i G. Kendall. "Evolutionary computation and games". IEEE Computational Intelligence Magazine 1, nr 1 (luty 2006): 10–18. http://dx.doi.org/10.1109/mci.2006.1597057.

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13

Mitchell, Melanie, i Charles E. Taylor. "Evolutionary Computation: An Overview". Annual Review of Ecology and Systematics 30, nr 1 (listopad 1999): 593–616. http://dx.doi.org/10.1146/annurev.ecolsys.30.1.593.

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14

De Jong, Kenneth A. "Evolutionary computation for discovery". Communications of the ACM 42, nr 11 (listopad 1999): 51–53. http://dx.doi.org/10.1145/319382.319392.

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15

Friedrich, Tobias, i Jonathan Rowe. "Genetic and Evolutionary Computation". Theoretical Computer Science 545 (sierpień 2014): 1. http://dx.doi.org/10.1016/j.tcs.2014.07.002.

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16

Friedrich, Tobias, Jun He, Thomas Jansen i Alberto Moraglio. "Genetic and Evolutionary Computation". Theoretical Computer Science 561 (styczeń 2015): 1–2. http://dx.doi.org/10.1016/j.tcs.2014.11.022.

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17

Doerr, Benjamin, i Thomas Jansen. "Theory of Evolutionary Computation". Algorithmica 59, nr 3 (9.11.2010): 299–300. http://dx.doi.org/10.1007/s00453-010-9472-3.

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18

Sendhoff, Bernhard, Mark Roberts i Xin Yao. "Evolutionary Computation Benchmarking Repository". IEEE Computational Intelligence Magazine 1, nr 4 (listopad 2006): 50–53. http://dx.doi.org/10.1109/ci-m.2006.248058.

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19

Fogel, D. B. "What is evolutionary computation?" IEEE Spectrum 37, nr 2 (luty 2000): 26–32. http://dx.doi.org/10.1109/6.819926.

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20

Du, Zhenyu. "Special issue on Intelligence Computation Evolutionary Computation: ICEV2018". Evolutionary Intelligence 12, nr 3 (31.07.2019): 321–22. http://dx.doi.org/10.1007/s12065-019-00271-0.

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21

Bonissone, P. P., R. Subbu, N. Eklund i T. R. Kiehl. "Evolutionary algorithms + domain knowledge = real-world evolutionary computation". IEEE Transactions on Evolutionary Computation 10, nr 3 (czerwiec 2006): 256–80. http://dx.doi.org/10.1109/tevc.2005.857695.

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22

Burgin, M., i E. Eberbach. "Evolutionary Automata: Expressiveness and Convergence of Evolutionary Computation". Computer Journal 55, nr 9 (29.09.2011): 1023–29. http://dx.doi.org/10.1093/comjnl/bxr099.

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23

Kohata, Naoki, Toru Yamaguchi, Takanobu Baba i Hideki Hashimoto. "Chaotic Evolutionary Parallel Computation on Intelligent Agents". Journal of Robotics and Mechatronics 10, nr 5 (20.10.1998): 424–30. http://dx.doi.org/10.20965/jrm.1998.p0424.

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This paper proposes evolutionary computation using chaotic dynamics rather than the conventional genetic algorithm (GA) for such intelligent agents as welfare robots. Proposed evolutionary computation applies chaotic retrieval to associative memory. We applied evolutionary computation to multiagent robots moving side by side in step. Evolutionary computation is basically parallel processing, so we implement its parallel processing algorithm on A-NET (Actors NETwork) parallel objectoriented computer to show usefulness of parallel processing in evolutionary computation.

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24

Karpov, V. E. "Methodological problems in evolutionary computation". Scientific and Technical Information Processing 40, nr 5 (grudzień 2013): 286–91. http://dx.doi.org/10.3103/s0147688213050031.

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25

Vanneschi, Leonardo, Luca Mussi i Stefano Cagnoni. "Hot topics in Evolutionary Computation". Intelligenza Artificiale 5, nr 1 (2011): 5–17. http://dx.doi.org/10.3233/ia-2011-0001.

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26

Ono, Isao. "An Introduction to Evolutionary Computation". IEEJ Transactions on Electronics, Information and Systems 122, nr 3 (2002): 324–29. http://dx.doi.org/10.1541/ieejeiss1987.122.3_324.

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27

MUNETOMO, Masaharu, i Hiroshi SOMEYA. "How to Apply Evolutionary Computation". Journal of The Institute of Electrical Engineers of Japan 132, nr 4 (2012): 204–7. http://dx.doi.org/10.1541/ieejjournal.132.204.

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28

OYAMA, Akira. "Evolutionary Computation in Space Engineering". Journal of The Institute of Electrical Engineers of Japan 132, nr 4 (2012): 208–11. http://dx.doi.org/10.1541/ieejjournal.132.208.

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29

Aguiar-Pulido, Vanessa, Marcos Gestal, Maykel Cruz-Monteagudo, Juan Rabunal, Julian Dorado i Cristian Munteanu. "Evolutionary Computation and QSAR Research". Current Computer Aided-Drug Design 9, nr 2 (1.06.2013): 206–25. http://dx.doi.org/10.2174/1573409911309020006.

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30

Kordon, Arthur. "Evolutionary computation at Dow Chemical". ACM SIGEVOlution 1, nr 3 (wrzesień 2006): 4–9. http://dx.doi.org/10.1145/1181964.1181965.

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31

Jin'no, Kenya. "Special issue on evolutionary computation". Nonlinear Theory and Its Applications, IEICE 10, nr 3 (2019): 279. http://dx.doi.org/10.1587/nolta.10.279.

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32

Handa, Hisashi, Hiroshi Kawakami i Osamu Katai. "Recent Advances in Evolutionary Computation". IEEJ Transactions on Electronics, Information and Systems 128, nr 3 (2008): 334–39. http://dx.doi.org/10.1541/ieejeiss.128.334.

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33

Bhandarkar, S. M., i Hui Zhang. "Image segmentation using evolutionary computation". IEEE Transactions on Evolutionary Computation 3, nr 1 (kwiecień 1999): 1–21. http://dx.doi.org/10.1109/4235.752917.

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34

Fogel, D. B. "Evolutionary Computation: A New Transactions". IEEE Transactions on Evolutionary Computation 1, nr 1 (kwiecień 1997): 1–2. http://dx.doi.org/10.1109/tevc.1997.585887.

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35

Lim, Dudy, Yaochu Jin, Yew-Soon Ong i Bernhard Sendhoff. "Generalizing Surrogate-Assisted Evolutionary Computation". IEEE Transactions on Evolutionary Computation 14, nr 3 (czerwiec 2010): 329–55. http://dx.doi.org/10.1109/tevc.2009.2027359.

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36

Miikkulainen, Risto, Paul Jarratt i Andrew Turner. "Evolutionary computation experts video collection". ACM SIGEVOlution 11, nr 3 (12.11.2018): 6. http://dx.doi.org/10.1145/3292044.3292046.

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37

Hong, Tzung-Pei, Ke-Yuan Huang i Wen-Yang Lin. "Adversarial Search by Evolutionary Computation". Evolutionary Computation 9, nr 3 (wrzesień 2001): 371–85. http://dx.doi.org/10.1162/106365601750406046.

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In this paper, we consider the problem of finding good next moves in two-player games. Traditional search algorithms, such as minimax and α-β pruning, suffer great temporal and spatial expansion when exploring deeply into search trees to find better next moves. The evolution of genetic algorithms with the ability to find global or near global optima in limited time seems promising, but they are inept at finding compound optima, such as the minimax in a game-search tree. We thus propose a new genetic algorithm-based approach that can find a good next move by reserving the board evaluation values of new offspring in a partial game-search tree. Experiments show that solution accuracy and search speed are greatly improved by our algorithm.

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38

Rothlauf, Franz, i David E. Goldberg. "Redundant Representations in Evolutionary Computation". Evolutionary Computation 11, nr 4 (grudzień 2003): 381–415. http://dx.doi.org/10.1162/106365603322519288.

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This paper discusses how the use of redundant representations influences the performance of genetic and evolutionary algorithms. Representations are redundant if the number of genotypes exceeds the number of phenotypes. A distinction is made between synonymously and non-synonymously redundant representations. Representations are synonymously redundant if the genotypes that represent the same phenotype are very similar to each other. Non-synonymously redundant representations do not allow genetic operators to work properly and result in a lower performance of evolutionary search. When using synonymously redundant representations, the performance of selectorecombinative genetic algorithms (GAs) depends on the modification of the initial supply. We have developed theoretical models for synonymously redundant representations that show the necessary population size to solve a problem and the number of generations goes with O(2kr/r), where kr is the order of redundancy and r is the number of genotypic building blocks (BB) that represent the optimal phenotypic BB. As a result, uniformly redundant representations do not change the behavior of GAs. Only by increasing r, which means overrepresenting the optimal solution, does GA performance increase. Therefore, non-uniformly redundant representations can only be used advantageously if a-priori information exists regarding the optimal solution. The validity of the proposed theoretical concepts is illustrated for the binary trivial voting mapping and the real-valued link-biased encoding. Our empirical investigations show that the developed population sizing and time to convergence models allow an accurate prediction of the empirical results.

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39

Harman, Mark. "Software Engineering Meets Evolutionary Computation". Computer 44, nr 10 (październik 2011): 31–39. http://dx.doi.org/10.1109/mc.2011.263.

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40

Mühlenbein, H., i Th Mahnig. "Evolutionary computation and Wright's equation". Theoretical Computer Science 287, nr 1 (wrzesień 2002): 145–65. http://dx.doi.org/10.1016/s0304-3975(02)00098-1.

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41

Yao, Xin. "Evolutionary computation comes of age". Cognitive Systems Research 1, nr 1 (grudzień 1999): 59–64. http://dx.doi.org/10.1016/s1389-0417(99)00006-6.

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42

Miranda, Vladimiro, Dipti Srinivasan i LM Proença. "Evolutionary computation in power systems". International Journal of Electrical Power & Energy Systems 20, nr 2 (luty 1998): 89–98. http://dx.doi.org/10.1016/s0142-0615(97)00040-9.

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43

Murawski, K., T. Arciszewski i K. De Jong. "Evolutionary Computation in Structural Design". Engineering with Computers 16, nr 3-4 (grudzień 2000): 275–86. http://dx.doi.org/10.1007/pl00013716.

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44

Claveria, Oscar, Enric Monte i Salvador Torra. "Evolutionary Computation for Macroeconomic Forecasting". Computational Economics 53, nr 2 (7.11.2017): 833–49. http://dx.doi.org/10.1007/s10614-017-9767-4.

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45

Wang, Jing-Zhong, Yingchieh Ho i Tsung-Ying Sun. "Fuzzy Scaled Mutation Evolutionary Computation". International Journal of Fuzzy Systems 18, nr 6 (18.02.2016): 1162–79. http://dx.doi.org/10.1007/s40815-016-0155-3.

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46

Reeves, Colin R. "Evolutionary computation: a unified approach". Genetic Programming and Evolvable Machines 8, nr 3 (26.07.2007): 293–95. http://dx.doi.org/10.1007/s10710-007-9035-9.

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47

Li, Xiaodong, Wenjian Luo i Xin Yao. "Theoretical foundations of evolutionary computation". Genetic Programming and Evolvable Machines 9, nr 2 (10.11.2007): 107–8. http://dx.doi.org/10.1007/s10710-007-9047-5.

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48

Bull, L. "On Model-Based Evolutionary Computation". Soft Computing - A Fusion of Foundations, Methodologies and Applications 3, nr 2 (23.09.1999): 76–82. http://dx.doi.org/10.1007/s005000050055.

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49

Zhang, Qingfu. "Knowledge incorporation in Evolutionary Computation". IEEE Computational Intelligence Magazine 1, nr 4 (listopad 2006): 58–59. http://dx.doi.org/10.1109/ci-m.2006.248069.

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50

Bhattacharyya, Siddhartha. "Evolutionary computation for database marketing". Journal of Database Marketing & Customer Strategy Management 10, nr 4 (lipiec 2003): 343–52. http://dx.doi.org/10.1057/palgrave.jdm.3240123.

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