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Books on the topic 'Evolutionary models'

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Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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1

Williams, Bryn Vaughan. Evolutionary neural networks: Models and applications. Birmingham: Aston University. Department of Computer Science and Mathematics, 1995.

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2

Evolutionary game theory. Cambridge, Mass: MIT Press, 1995.

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3

Bulmer, M. G. Theoretical evolutionary ecology. Sunderland, Mass: Sinauer Associates, Inc, 1994.

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4

Jonathan, Raper, ed. Spatial evolutionary modeling. New York: Oxford University Press, 2000.

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5

Theoretical evolutionary ecology. Sunderland, Mass: Sinauer Associates, 1994.

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6

Ehteram, Mohammad, Zohreh Sheikh Khozani, Saeed Soltani-Mohammadi, and Maliheh Abbaszadeh. Estimating Ore Grade Using Evolutionary Machine Learning Models. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8106-7.

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7

W, Feldman Marcus, and Karlin Samuel 1923-, eds. Mathematical evolutionary theory. Princeton, N.J: Princeton University Press, 1989.

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8

Mayer, David G. Evolutionary algorithms and agricultural systems. Boston: Kluwer Academic Publishers, 2002.

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9

Tanskanen, Pasi. The evolutionary structural optimization (ESO) method: Theoretical aspects and the modified evolutionary structural optimization (MESO) method. Lappeenranta, Finland: Lappeenranta University of Technology, 2000.

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10

Codon evolution: Mechanisms and models. Oxford: Oxford University Press, 2012.

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11

Rana, Fazale. Origins of life: Biblical and evolutionary models face off. Covina, CA: RTB Press, 2013.

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12

Evolutionary genetics. 2nd ed. Oxford: Oxford University Press, 1998.

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13

Evolutionary genetics. Oxford: Oxford University Press, 1989.

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14

Bäck, Thomas. Evolutionary algorithms in theory and practice: Evolution strategies, evolutionary programming, genetic algorithms. New York: Oxford University Press, 1996.

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15

Hendy, M. D. Discrete fourier analysis for evolutionary trees. Palmerston North, N.Z: School of Mathematical and Information Sciences, Massey University, 1992.

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16

Andrew, Adamatzky, and Komosinski Maciej, eds. Artificial life models in software. 2nd ed. Dordrecht: Springer, 2009.

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17

Progress and prospects in evolutionary biology: The Drosophila model. New York: Oxford University Press, 1997.

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18

M, Svirezhev I͡U. Fundamentals of mathematical evolutionary genetics. Dordrecht: Kluwer Academic Publishers, 1990.

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19

Ulf, Johansson. Obtaining accurate and comprehensible data mining models: An evolutionary approach. Linko ping: Department of Computer and Information Science, Linko pings universitet, 2007.

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20

Olofsson, Kjell. Spectral evolutionary synthesis models of metal-poor star forming regions. Uppsala: Uppsala Astronomical Observatory, 1988.

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21

L, Casti J., and Karlqvist Anders, eds. Cooperation and conflict in general evolutionary processes. New York: Wiley, 1995.

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22

1945-, Sigmund Karl, ed. Evolutionary games and population dynamics. Cambridge: Cambridge University Press, 1998.

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23

1966-, Clark David E., ed. Evolutionary algorithms in molecular design. Weinheim: Wiley-VCH, 2000.

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24

Wolfson, Michael C. XEcon: An experimental/evolutionary model of economic growth. Ottawa, Ont: Publications Review Committee, Analytical Studies Branch, Statistics Canada, 1995.

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25

Loomis, D. G. The genetic cycle of life: Nanohistory and macro evolution. Mount Stewart, PE: DGL Publications, 2005.

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26

The stability concept of evolutionary game theory: A dynamic approach. Berlin: Springer-Verlag, 1992.

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27

Probability models for DNA sequence evolution. 2nd ed. New York: Springer, 2008.

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28

Probability models for DNA sequence evolution. New York: Springer, 2002.

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29

Boland, Lawrence A. Equilibrium models vs. evolutionary economic models. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190274320.003.0012.

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This chapter examines the extent to which models based on evolutionary economics can provide a worthy alternative to neoclassical equilibrium models. The chapter discusses the difference between Darwinian and non-Darwinian evolutionary economic models. The chapter includes a discussion of Armen Alchian’s 1950 article that he says is erroneously identified as evolutionary economics. The works of evolutionary economists Ulrich Witt, Jack Vromen, Richard Nelson and Sidney are explained and critically examined. The chapter also considers the question of whether evolutionary economics can ever displace equilibrium economics. Some current evolutionary economic model builders have serious doubts. The chapter concludes with some speculations about going beyond the consideration of the individual firm to include sociological aspects of consumer preference.

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30

McGuire, Michael, and Alfonso Troisi. Evolutionary Models of Depression. Oxford University Press, 2015. http://dx.doi.org/10.1093/med:psych/9780195116731.003.0007.

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This chapter begins with a brief discussion of three topics: models that include more than one variable (the 15% principle), conditions grouped by behavior systems, and sexual selection. These topics set the context for the review of models of depression that appears in the second half of the chapter.

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31

Jones, Adam. C++ for Biologists: Evolutionary Models. Independently Published, 2018.

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32

Pease, Craig M. Models of coevolution and evolutionary epidemiology. 1985.

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33

Bueno, Juan. Molecular Evolutionary Models in Drug Discovery. Elsevier Science & Technology, 2020.

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34

Molecular Evolutionary Models in Drug Discovery. Elsevier, 2020. http://dx.doi.org/10.1016/c2018-0-01789-2.

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35

Bueno, Juan. Molecular Evolutionary Models in Drug Discovery. Elsevier Science & Technology Books, 2020.

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36

Hui, Cang, Pietro Landi, Henintsoa Onivola Minoarivelo, and Andriamihaja Ramanantoanina. Ecological and Evolutionary Modelling. Springer, 2018.

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37

Jeffares, Ben, and Kim Sterelny. Evolutionary Psychology. Edited by Eric Margolis, Richard Samuels, and Stephen P. Stich. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780195309799.013.0020.

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The article presents several models of evolutionary psychology. Nativist evolutionary psychology is built around a most important insight that ordinary human decision-making has a high cognitive load. Evolutionary nativists defend a modular solution to the problem of information load on human decision-making. Human minds comprises of special purpose cognitive devices or modules. One of the modules is a language module, a module for interpreting the thoughts and intentions of others, another is a ‘naive physics’ module for causal reasoning about sticks, stones, and similar inanimate objects, a natural history module for ecological decisions, and a social exchange module for monitoring economic interactions with peers. These modules evolved in response to the distinctive, independent, and recurring problems faced by the ancestors. Domain specific modules handle information about human language, human minds, inanimate causal interactions, the biological world, and other constant adaptive demands faced by human ancestors. Nativist evolutionary psychologists have turned to moral decision making, arguing that cross-cultural moral judgments are invariant in an unexpected way. Natural selection can build and equip a special purpose module only if the information an agent needs to know is stable over evolutionary time. Automatized skills are an alternative means of coping with high-load problems. These skills are phenomenologically rather like modules, but they have very different developmental and evolutionary histories.

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38

Del Giudice, Marco. Evolutionary Psychopathology. Oxford University Press, 2018. http://dx.doi.org/10.1093/med-psych/9780190246846.001.0001.

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This book presents a unified approach to evolutionary psychopathology, and advances an integrative framework for the analysis and classification of mental disorders based on the concepts of life history theory. The framework does not aim to replace existing evolutionary models of specific disorders—which are reviewed and critically discussed in the book—but to connect them in a broader perspective and explain the large-scale patterns of risk and comorbidity that characterize psychopathology. The life history framework permits a seamless integration of mental disorders with normative individual differences in personality and cognition, and offers new conceptual tools for the analysis of developmental, genetic, and neurobiological data. The concepts synthesized in the book are used to derive a new taxonomy of mental disorders, the fast-slow-defense (FSD) model. The FSD model is the first classification system explicitly based on evolutionary concepts, a biologically grounded alternative to transdiagnostic models based on empirical correlations between symptoms. The book reviews a wide range of common mental disorders, discusses their classification in the FSD model, and identifies functional subtypes within existing diagnostic categories.

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39

Ehteram, Mohammad, Zohreh Sheikh Khozani, Saeed Soltani-Mohammadi, and Maliheh Abbaszadeh. Estimating Ore Grade Using Evolutionary Machine Learning Models. Springer, 2023.

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40

Smith, Kenny. Why formal models are useful for evolutionary linguists. Oxford University Press, 2011. http://dx.doi.org/10.1093/oxfordhb/9780199541119.013.0060.

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41

Nowak, Martin A. Evolutionary Dynamics: Exploring the Equations of Life. Harvard University Press, 2006.

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42

Evolutionary Dynamics: Exploring the Equations of Life. Belknap Press, 2006.

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43

Feldman, Marcus W. Mathematical Evolutionary Theory. Princeton University Press, 2014.

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44

Feldman, Marcus W. Mathematical Evolutionary Theory. Princeton University Press, 2016.

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45

Mathematical Evolutionary Theory. Princeton University Press, 1989.

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46

Feldman, Marcus W. Mathematical Evolutionary Theory. Princeton University Press, 2014.

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47

Morris, A. Kimo. A model of trophic evolutionary pathways. 1997.

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48

Andrew, Adamatzky, and Komosinski Maciej, eds. Artificial life models in software. London: Springer, 2005.

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49

Andrew, Adamatzky, and Komosinski Maciej, eds. Artificial life models in software. New York: Springer, 2005.

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50

Cannarozzi, Gina M., and Adrian Schneider. Codon Evolution: Mechanisms and Models. Oxford University Press, 2012.

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