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Books on the topic 'Machine theory of collective intelligence'

Author: Grafiati

Published: 10 December 2022

Last updated: 31 July 2025

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1

Wieringa, Roel. Machine intelligence and explanation. 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. 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. M.I.T. Press, 1989.

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4

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

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5

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

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6

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

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7

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

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8

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

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9

International Workshop on Implementing Automata (2nd 1997 London, Ont.). Automata implementation: Second International Workshop on Implementing Automata, WIA '97, London, Ontario, Canada, September 18-20, 1997 : revised papers. Springer, 1998.

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10

1964-, Auer Peter, Meir Ron, and LINK (Online service), eds. Learning theory: 18th annual conference on learning theory, COLT 2005, Bertinoro, Italy, June 27-30 : proceedings. Springer, 2005.

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11

1957-, Clark Andy, and Toribio Josefa, eds. Machine intelligence: Perspectives on the computational model. Garland Pub., 1998.

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12

1967-, Jiang Xia, ed. Contemporary artificial intelligence. Taylor & Francis, 2012.

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13

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

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14

James, Stewart, Michael Rovatsos, Anton Nijholt, Daniele Miorandi, and Vincenzo Maltese. Social Collective Intelligence: Combining the Powers of Humans and Machines to Build a Smarter Society. Springer, 2014.

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15

James, Stewart, Michael Rovatsos, Anton Nijholt, Daniele Miorandi, and Vincenzo Maltese. Social Collective Intelligence: Combining the Powers of Humans and Machines to Build a Smarter Society. Springer International Publishing AG, 2016.

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16

James, Stewart. Social Collective Intelligence: Combining the Powers of Humans and Machines to Build a Smarter Society. Springer, 2014.

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17

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

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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, Incorporated, John, 2016.

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19

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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20

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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21

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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22

Davies, E. R. Machine Vision : Theory, Algorithms, Practicalities. Morgan Kaufmann, 2004.

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23

Davies, E. R. Machine Vision : Theory, Algorithms, Practicalities. 3rd ed. Morgan Kaufmann, 2004.

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24

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

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25

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

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26

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

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27

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

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28

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

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29

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

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30

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

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31

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

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32

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

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33

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

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34

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

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35

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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36

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

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37

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

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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

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

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40

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

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41

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

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42

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

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43

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

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44

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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45

Najim, K., and A. S. Poznyak. Learning Automata: Theory and Applications. Elsevier Science & Technology Books, 2014.

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46

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

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47

Shen, Jun, Geng Sun, and Jiayin Lin. Adaptive Micro Learning - Using Fragmented Time to Learn. World Scientific Publishing Co Pte Ltd, 2020.

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48

Antiga, Luca Pietro Giovanni, Eli Stevens, and Thomas Viehmann. Deep Learning with Pytorch. Manning Publications Co. LLC, 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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