Behavioral computational social science [electronic resource] / Riccardo Boero.

Boero, Riccardo, author.
Chichester, West Sussex, UK : Wiley, 2015.
1 online resource (x, 188 pages).
Wiley series in computational and quantitative social science.
Wiley series in computational and quantitative social science

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Social sciences -- Mathematical models.
Social sciences -- Data processing.
Title Page; Copyright Page; Contents; Preface; Chapter 1 Introduction: Toward behavioral computational social science; 1.1 Research strategies in CSS; 1.2 Why behavioral CSS; 1.3 Organization of the book; PART I CONCEPTS AND METHODS; Chapter 2Explanation in computational social science; 2.1 Concepts; 2.1.1 Causality; 2.1.2 Data; 2.2 Methods; 2.2.1 ABMs; 2.2.2 Statistical mechanics, system dynamics, and cellular automata; 2.3 Tools; 2.4 Critical issues: Uncertainty, model communication; Chapter 3Observation and explanation in behavioral sciences; 3.1 Concepts; 3.2 Observation methods
3.2.1 Naturalistic observation and case studies3.2.2 Surveys; 3.2.3 Experiments and quasiexperiments; 3.3 Tools; 3.4 Critical issues: Induced responses, external validity, and replicability; Chapter 4Reasons for integration; 4.1 The perspective of agent-based modelers; 4.2 The perspective of behavioral social scientists; 4.3 The perspective of social sciences in general; PART II BEHAVIORAL COMPUTATIONAL SOCIAL SCIENCE IN PRACTICE; Chapter 5Behavioral agents; 5.1 Measurement scales of data; 5.2 Model calibration; 5.2.1 Single decision variable and simple decision function
5.2.2 Multiple decision variables and multilevel decision trees5.3 Model classification; 5.4 Critical issues: Validation, uncertainty modeling; Chapter 6Sophisticated agents; 6.1 Common features of sophisticated agents; 6.2 Cognitive processes; 6.2.1 Reinforcement learning; 6.2.2 Other models of bounded rationality; 6.2.3 Nature-inspired algorithms; 6.3 Cognitive structures; 6.3.1 Middle-level structures; 6.3.2 Rich cognitive models; 6.4 Critical issues: Calibration, validation, robustness, social interface; Chapter 7Social networks and other interaction structures
7.1 Essential elements of SNA7.2 Models for the generation of social networks; 7.3 Other kinds of interaction structures; 7.4 Critical issues: Time and behavior; Chapter 8An example of application; 8.1 The social dilemma; 8.1.1 The theory; 8.1.2 Evidence; 8.1.3 Our research agenda; 8.2 The original experiment; 8.3 Behavioral agents; 8.3.1 Fixed effects model; 8.3.2 Random coefficients model; 8.3.3 First differences model; 8.3.4 Ordered probit model with individual dummies; 8.3.5 Multilevel decision trees; 8.3.6 Classified heuristics; 8.4 Learning agents; 8.5 Interaction structures
8.6 Results: Answers to a few research questions8.6.1 Are all models of agents capable of replicating the experiment?; 8.6.2 Was the experiment influenced by chance?; 8.6.3 Do economic incentives work?; 8.6.4 Why does increasing group size generate more cooperation?; 8.6.5 What happens with longer interaction?; 8.6.6 Does a realistic social network promote cooperation?; 8.7 Conclusions; Appendix Technical guide to the example model; A.1 The interface; A.2 The code; A.2.1 Variable declaration; A.2.2 Simulation setup; A.2.3 Running the simulation; A.2.4 Decision-making
Includes bibliographical references and index.
Electronic reproduction. Hoboken, N.J. Available via World Wide Web.
Description based on print version record and CIP data provided by publisher.
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Acquired for the Penn Libraries with assistance from the Esther F. Kantrowitz & Lionel Kantrowitz Collection Endowment Fund.
Wiley InterScience (Online service)
Esther F. Kantrowitz & Lionel Kantrowitz Collection Endowment Fund.
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Print version: Boero, Riccardo. Behavioral computational social science
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