Behavioral computational social science

Intro -- 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 2 Explanation 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 3 Observation and explanation in behavioral sciences -- 3.1 Concepts -- 3.2 Observation methods -- 3.2.1 Naturalistic observation and case studies -- 3.2.2 Surveys -- 3.2.3 Experiments and quasiexperiments -- 3.3 Tools -- 3.4 Critical issues: Induced responses, external validity, and replicability -- Chapter 4 Reasons 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 5 Behavioral 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 trees -- 5.3 Model classification -- 5.4 Critical issues: Validation, uncertainty modeling -- Chapter 6 Sophisticated 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 7 Social networks and other interaction structures.

"This book is organized in two parts: the first part introduces the reader to all the concepts, tools and references that are required to start conducting research in behavioral computational social science. The methodological reasons for integrating the two approaches are also presented from the individual and separated viewpoints of the two approaches.The second part of the book, presents all the advanced methodological and technical aspects that are relevant for the proposed integration. Several contributions which effectively merge the computational and the behavioral approaches are presented and discussed throughout"--

"Provides a unified approach to social research, integrating both agent-based models and behavioral studies.Introduces the reader to all the concepts, tools and references that are required for conducting research in behavioral computational social science"--