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1

Payne, Stephen J., e Andrew Howes. Adaptive Interaction. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-031-02199-2.

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2

Nikiforov, Vladimir, e Dmitry Gerasimov. Adaptive Regulation. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96091-9.

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3

Diniz, Paulo S. R. Adaptive Filtering. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-68606-6.

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4

Landau, I. D., R. Lozano e M. M’Saad. Adaptive Control. London: Springer London, 1998. http://dx.doi.org/10.1007/978-0-85729-343-5.

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5

Wagg, David J., Ian P. Bond, Paul M. Weaver e Michael I. Friswell, a cura di. Adaptive Structures. Chichester, UK: John Wiley & Sons, Ltd, 2007. http://dx.doi.org/10.1002/9780470512067.

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6

Pollock, Jeffrey T., e Ralph Hodgson. Adaptive Information. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2004. http://dx.doi.org/10.1002/0471714216.

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7

Landau, Ioan Doré, Rogelio Lozano, Mohammed M'Saad e Alireza Karimi. Adaptive Control. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-664-1.

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8

Johnston, Norm. Adaptive Marketing. New York: Palgrave Macmillan US, 2015. http://dx.doi.org/10.1057/9781137462930.

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9

Mareels, Iven, e Jan Willem Polderman. Adaptive Systems. Boston, MA: Birkhäuser Boston, 1996. http://dx.doi.org/10.1007/978-0-8176-8142-5.

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10

Tertychny-Dauri, Vladimir Yu. Adaptive Mechanics. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-007-0787-0.

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11

Lehman, Jill Fain. Adaptive Parsing. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3622-2.

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12

Diniz, Paulo S. R. Adaptive Filtering. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-29057-3.

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13

Diniz, Paulo S. R. Adaptive Filtering. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-4106-9.

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14

Diniz, Paulo Sergio Ramirez. Adaptive Filtering. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4419-8660-3.

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15

Moschytz, George S., e Markus Hofbauer. Adaptive Filter. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-18250-1.

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16

Schmidt, Louis A., e Kristie L. Poole, a cura di. Adaptive Shyness. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38877-5.

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17

Dodge, Yadolah, e Jana Jurečková. Adaptive Regression. New York, NY: Springer New York, 2000. http://dx.doi.org/10.1007/978-1-4419-8766-2.

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18

Gross, Thilo, e Hiroki Sayama, a cura di. Adaptive Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01284-6.

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19

Ramirez, Paulo Sergio. Adaptive Filtering. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-3637-3.

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20

Allweyer, Thomas. Adaptive Geschäftsprozesse. Wiesbaden: Gabler Verlag, 1998. http://dx.doi.org/10.1007/978-3-663-09209-4.

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21

Reschly, Daniel J. Adaptive behavior. Tallahassee, Fla: Florida Dept. of Education, Division of Public Schools, Bureau of Education for Exceptional Students, 1987.

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22

Sayed, Ali H. Adaptive filters. Hoboken, NJ: J. Wiley & Sons, 2008.

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23

Baker, John, e Corey Seemiller. Adaptive Leadership. 1 Oliver’s Yard, 55 City Road, London EC1Y 1SP United Kingdom United States: SAGE Publications, Inc., 2023. http://dx.doi.org/10.4135/9781071908105.

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24

Thompson, Steven K. Adaptive sampling. New York: Wiley, 1996.

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25

Preiser, Wolfgang F. E., Andrea E. Hardy e Jacob J. Wilhelm, a cura di. Adaptive Architecture. New York : Routledge, 2017.: Routledge, 2017. http://dx.doi.org/10.4324/9781315627113.

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26

Björn, Wittenmark, a cura di. Adaptive control. Reading, Mass: Addison-Wesley, 1989.

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27

Lee, Frederick W. Adaptive radar. Washington, DC: Naval Research Laboratory, 1991.

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28

N, Cowan C. F., Grant Peter M e Adams P. F, a cura di. Adaptive filters. Englewood Cliffs, N.J: Prentice-Hall, 1985.

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29

Dragoș, Zaharia, a cura di. Adaptive arrays. Amsterdam: Elsevier, 1989.

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30

1958-, Lee Tong Heng, Ho Weng K e Instrument Society of America, a cura di. Adaptive control. Research Triangle Park, N.C: Instrument Society of America, 1993.

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31

Nisbet, Ewan. Adaptive firewalls. Oxford: Oxford Brookes University, 2002.

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32

Lee, Frederick W. Adaptive radar. Washington, DC: Naval Research Laboratory, 1991.

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33

Åström, Karl J. Adaptive control. 2a ed. Mineola, N.Y: Dover Publications, 2008.

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34

Åström, Karl J. Adaptive control. 2a ed. Mineola, N.Y: Dover Publications, 2008.

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35

Landau, Yoan D. Adaptive control. London: Springer, 1998.

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36

Sayed, Ali H. Fundamentals of Adaptive Filtering. Wiley & Sons, Incorporated, John, 2008.

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37

Fundamentals of adaptive filtering. New York: IEEE Press, 2003.

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38

(Editor), WENDY SCHRUPP, LEE REEDY (Illustrator) e DEACON CHAPIN (Photographer), a cura di. Psia Adaptive Manual (ADAPTIVE MANUAL). PSIA, 1997.

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39

Schwartz, Bennett L., Mark L. Howe, Michael P. Toglia e Henry Otgaar, a cura di. What Is Adaptive about Adaptive Memory? Oxford University Press, 2013. http://dx.doi.org/10.1093/acprof:oso/9780199928057.001.0001.

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40

What Is Adaptive about Adaptive Memory? Oxford University Press, 2013.

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41

Toglia, Michael P., Mark L. Howe, Bennett L. Schwartz e Henry Otgaar. What Is Adaptive about Adaptive Memory? Oxford University Press, Incorporated, 2013.

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42

What Is Adaptive about Adaptive Memory? Oxford University Press, Incorporated, 2013.

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43

Eichler, Julian. Adaptive Intelligenz, Adaptives Problemlösen und Lernprozesse in Organisationen. GRIN Verlag GmbH, 2014.

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44

Bacon, Terry R., e Laurie Voss. Adaptive Coaching. Brealey Publishing, Nicholas, 2011.

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45

Sayed, Ali H. Adaptive Filters. Wiley & Sons, Incorporated, John, 2008.

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46

Mitchell, Ferd H., e Cheryl C. Mitchell. Adaptive Administration. Routledge, 2015. http://dx.doi.org/10.1201/b19193.

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47

Kaber, David B. Adaptive Automation. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199757183.013.0041.

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48

Tasse, Marc J. Adaptive Behavior. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780195398786.013.013.0009.

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49

Brunner, Ronald D., e Amanda H. Lynch. Adaptive Governance. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.601.

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Abstract (sommario):
Adaptive governance is defined by a focus on decentralized decision-making structures and procedurally rational policy, supported by intensive natural and social science. Decentralized decision-making structures allow a large, complex problem like global climate change to be factored into many smaller problems, each more tractable for policy and scientific purposes. Many smaller problems can be addressed separately and concurrently by smaller communities. Procedurally rational policy in each community is an adaptation to profound uncertainties, inherent in complex systems and cognitive constraints, that limit predictability. Hence planning to meet projected targets and timetables is secondary to continuing appraisal of incremental steps toward long-term goals: What has and hasn’t worked compared to a historical baseline, and why? Each step in such trial-and-error processes depends on politics to balance, if not integrate, the interests of multiple participants to advance their common interest—the point of governance in a free society. Intensive science recognizes that each community is unique because the interests, interactions, and environmental responses of its participants are multiple and coevolve. Hence, inquiry focuses on case studies of particular contexts considered comprehensively and in some detail.Varieties of adaptive governance emerged in response to the limitations of scientific management, the dominant pattern of governance in the 20th century. In scientific management, central authorities sought technically rational policies supported by predictive science to rise above politics and thereby realize policy goals more efficiently from the top down. This approach was manifest in the framing of climate change as an “irreducibly global” problem in the years around 1990. The Intergovernmental Panel on Climate Change (IPCC) was established to assess science for the Conference of the Parties (COP) to the U.N. Framework Convention on Climate Change (UNFCCC). The parties negotiated the Kyoto Protocol that attempted to prescribe legally binding targets and timetables for national reductions in greenhouse gas emissions. But progress under the protocol fell far short of realizing the ultimate objective in Article 1 of the UNFCCC, “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference in the climate system.” As concentrations continued to increase, the COP recognized the limitations of this approach in Copenhagen in 2009 and authorized nationally determined contributions to greenhouse gas reductions in the Paris Agreement in 2015.Adaptive governance is a promising but underutilized approach to advancing common interests in response to climate impacts. The interests affected by climate, and their relative priorities, differ from one community to the next, but typically they include protecting life and limb, property and prosperity, other human artifacts, and ecosystem services, while minimizing costs. Adaptive governance is promising because some communities have made significant progress in reducing their losses and vulnerability to climate impacts in the course of advancing their common interests. In doing so, they provide field-tested models for similar communities to consider. Policies that have worked anywhere in a network tend to be diffused for possible adaptation elsewhere in that network. Policies that have worked consistently intensify and justify collective action from the bottom up to reallocate supporting resources from the top down. Researchers can help realize the potential of adaptive governance on larger scales by recognizing it as a complementary approach in climate policy—not a substitute for scientific management, the historical baseline.
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50

Staddon, John E. R. Adaptive Dynamics. The MIT Press, 2001. http://dx.doi.org/10.7551/mitpress/1092.001.0001.

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