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Books on the topic 'Machine theory of collective intelligence'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Wieringa, Roel. Machine intelligence and explanation. Delft: Eburon, 1987.

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2

Bajpai, Manish Kumar, Koushlendra Kumar Singh, and George Giakos, eds. Machine Vision and Augmented Intelligence—Theory and Applications. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5078-9.

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3

Hillis, W. Daniel. The connection machine. Cambridge: M.I.T. Press, 1989.

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4

The connection machine. Cambridge, Mass: MIT Press, 1985.

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5

Kahraman, Cengiz, and Gülgün Kayakutlu, eds. Energy Management—Collective and Computational Intelligence with Theory and Applications. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75690-5.

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6

The emergence of artificial cognition: An introduction to collective learning. Singapore: World Scientific, 1993.

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7

Najim, K. Learning automata: Theory and applications. Oxford, OX, U.K: Pergamon, 1994.

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8

Okun, Oleg. Ensembles in Machine Learning Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011.

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9

AGI Conference (1st 2008 University of Memphis). Artificial general intelligence, 2008: Proceedings of the First AGI Conference. Amsterdam: IOS Press, 2008.

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10

Nadia, Nedjah, and Macedo Mourelle Luiza de, eds. Evolvable machines: Theory & practice. Berlin: Springer, 2005.

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11

1940-, Wood Derick, and Yü Sheng, eds. Automata implementation: Second International Workshop on Implementing Automata, WIA'97, London, Ontario, Canada, September 18-20, 1997 : revised papers. Berlin: Springer, 1998.

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12

1976-, Elkind Edith, and Wooldridge Michael J. 1966-, eds. Computational aspects of cooperative game theory. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool, 2012.

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13

Virkumar, Vazirani Umesh, ed. An introduction to computational learning theory. Cambridge, Mass: MIT Press, 1994.

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14

Guoying, Zhao, Cheng Li, Pietikäinen Matti, and SpringerLink (Online service), eds. Machine Learning for Vision-Based Motion Analysis: Theory and Techniques. London: Springer-Verlag London Limited, 2011.

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15

E, Nicholson Ann, ed. Bayesian artificial intelligence. Boca Raton, Fla: Chapman & Hall/CRC, 2004.

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16

Mundy, Joy, and Ralph Kimball. Kimball Group Reader: Relentlessly Practical Tools for Data Warehousing and Business Intelligence Remastered Collection. Wiley & Sons, Incorporated, John, 2016.

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17

Mundy, Joy, and Ralph Kimball. Kimball Group Reader: Relentlessly Practical Tools for Data Warehousing and Business Intelligence Remastered Collection. Wiley & Sons, Limited, John, 2016.

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18

Mundy, Joy, and Ralph Kimball. Kimball Group Reader: Relentlessly Practical Tools for Data Warehousing and Business Intelligence Remastered Collection. Wiley & Sons, Limited, John, 2016.

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19

Wolpert, David, and NASA Technical Reports Server (NTRS). Theory of Collective Intelligence. BiblioGov, 2013.

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20

Farrell, P. G., J. R. Forrest, and E. R. Davies. Machine Vision: Theory, Algorithms, Practicalities. Elsevier Science & Technology Books, 2014.

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21

Davies, E. R. Machine Vision: Theory, Algorithms, Practicalities. Elsevier Science & Technology Books, 2004.

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22

Rao, C. R., and Venu Govindaraju. Machine Learning: Theory and Applications. Elsevier Science & Technology Books, 2013.

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23

Rao, C. R., and Venu Govindaraju. Machine Learning: Theory and Applications. Elsevier Science & Technology Books, 2013.

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24

Overgaard, Morten. National Collective Intelligence: A Metamodern Theory of Politics. Independently Published, 2019.

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25

Ridley, David. Method of Democracy: John Dewey's Theory of Collective Intelligence. Lang AG International Academic Publishers, Peter, 2020.

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26

Ridley, David. Method of Democracy: John Dewey's Theory of Collective Intelligence. Lang AG International Academic Publishers, Peter, 2021.

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27

Ridley, David. Method of Democracy: John Dewey's Theory of Collective Intelligence. Lang AG International Academic Publishers, Peter, 2021.

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28

Ridley, David. Method of Democracy: John Dewey's Theory of Collective Intelligence. Lang AG International Academic Publishers, Peter, 2021.

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29

Reddy, Sandeep. Artificial Intelligence. Taylor & Francis Group, 2021.

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30

Reddy, Sandeep. Artificial Intelligence. Taylor & Francis Group, 2020.

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31

Vermesan, Ovidiu, and Joël Bacquet. Cognitive Hyperconnected Digital Transformation: Internet of Things Intelligence Evolution. River Publishers, 2022.

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32

Cognitive Hyperconnected Digital Transformation: Internet of Things Intelligence Evolution. River Publishers, 2017.

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33

Vermesan, Ovidiu, and Joel Bacquet. Cognitive Hyperconnected Digital Transformation: Internet of Things Intelligence Evolution. River Publishers, 2017.

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34

Vermesan, Ovidiu, and Joël Bacquet. Cognitive Hyperconnected Digital Transformation: Internet of Things Intelligence Evolution. River Publishers, 2022.

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35

Vermesan, Ovidiu, and Joël Bacquet. Cognitive Hyperconnected Digital Transformation: Internet of Things Intelligence Evolution. River Publishers, 2022.

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36

Holmes, Dawn E. Innovations in Machine Learning: Theory and Applications. Springer London, Limited, 2006.

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37

Holmes, Dawn E. Innovations in Machine Learning: Theory and Applications. Springer, 2010.

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38

Machine Intelligence: Quo Vadis? (Advances in Fuzzy Systems- Applications and Theory). World Scientific Publishing Company, 2004.

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39

Murphy, Martin J., Issam El Naqa, and Ruijiang Li. Machine Learning in Radiation Oncology: Theory and Applications. Springer, 2015.

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40

Murphy, Martin J., Issam El Naqa, and Ruijiang Li. Machine Learning in Radiation Oncology: Theory and Applications. Springer London, Limited, 2015.

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41

Murphy, Martin J., Issam El Naqa, and Ruijiang Li. Machine Learning in Radiation Oncology: Theory and Applications. Springer, 2016.

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42

Kahraman, Cengiz, and Gülgün Kayakutlu. Energy Management―Collective and Computational Intelligence with Theory and Applications. Springer, 2018.

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43

Kahraman, Cengiz, and Gülgün Kayakutlu. Energy Management―Collective and Computational Intelligence with Theory and Applications. Springer, 2018.

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44

Jantke, Klaus P., S. Kobayashi, and Etsuji Tomita. Algorithmic Learning Theory: Proceedings (Lecture Notes in Artificial Intelligence). Springer, 1993.

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45

Sgurev, Vassil, Vladimir Jotsov, and Vincenzo Piuri. Learning Systems: From Theory to Practice. Springer, 2019.

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46

Sgurev, Vassil, Vladimir Jotsov, and Vincenzo Piuri. Learning Systems: From Theory to Practice. Springer, 2018.

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47

Henrion, Max, L. N. Kanal, and P. P. Bonissone. Uncertainty in Artificial Intelligence, 6 (Machine Intelligence and Pattern Recognition). Elsevier Science Pub Co, 1991.

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48

Campesato, Oswald. Angular and Deep Learning Pocket Primer. Mercury Learning & Information, 2020.

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49

Campesato, Oswald. Angular and Deep Learning Pocket Primer. Mercury Learning & Information, 2020.

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50

Campesato, Oswald. Angular and Deep Learning Pocket Primer. Mercury Learning & Information, 2020.

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