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Modeling Populations of Adaptive Individuals$
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Steven F. Railsback and Bret C. Harvey

Print publication date: 2020

Print ISBN-13: 9780691195285

Published to Princeton Scholarship Online: January 2021

DOI: 10.23943/princeton/9780691195285.001.0001

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Conclusions and Outlook

Conclusions and Outlook

Chapter:
(p.154) Chapter 12 Conclusions and Outlook
Source:
Modeling Populations of Adaptive Individuals
Author(s):
Steven F. Railsback, Bret C. Harvey
Publisher:
Princeton University Press
DOI:10.23943/princeton/9780691195285.003.0012

This chapter summarizes the key characteristics of the approach for modeling, studying, and understanding populations and communities of adaptive individuals described here, and outlines the lessons learned from all the models examined in this book. Many of these characteristics are shared with individual-based population modeling in general. First, state- and prediction-based theory (SPT) explicitly includes multiple levels of organization: models of individual adaptive behavior explain population and higher-level dynamics. Second, doing theory is more productive when one models real systems and applied problems. Third, the approach relies on simulation, approximation, and updating instead of traditional mathematical frameworks. Fourth, SPT and the theory testing cycle facilitate beneficial linkage of modeling and empirical work. Finally, the pattern-oriented theory development cycle gives ecologists the power of strong inference.

Keywords:   population modeling, adaptive individuals, individual-based population modeling, state-based theory, prediction-based theory, individual adaptive behavior, theory testing cycle, pattern-oriented theory development, ecologists, ecology

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