LEADER 06064nam 2200757 450 001 9910131482203321 005 20200520144314.0 010 $a1-119-10615-X 010 $a1-119-10617-6 010 $a1-119-10616-8 035 $a(CKB)3710000000451192 035 $a(EBL)2030742 035 $a(SSID)ssj0001530246 035 $a(PQKBManifestationID)12505039 035 $a(PQKBTitleCode)TC0001530246 035 $a(PQKBWorkID)11523735 035 $a(PQKB)10238046 035 $a(PQKBManifestationID)16226515 035 $a(PQKB)20515878 035 $a(DLC) 2015030459 035 $a(Au-PeEL)EBL4041028 035 $a(CaPaEBR)ebr11081200 035 $a(CaONFJC)MIL816299 035 $a(Au-PeEL)EBL2030742 035 $a(PPN)191455377 035 $a(MiAaPQ)EBC4041028 035 $a(OCoLC)915311978 035 $a(EXLCZ)993710000000451192 100 $a20150810h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aBehavioral computational social science /$fRiccardo Boero 205 $a1st ed. 210 1$aChichester, England :$cWiley,$d2015. 210 4$dİ2015 215 $a1 online resource (201 p.) 225 1 $aWiley Series in Computational and Quantitative Social Science 300 $aDescription based upon print version of record. 311 $a1-118-65730-6 320 $aIncludes bibliographical references and index. 327 $aTitle 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 327 $a3.2.1 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 327 $a5.2.2 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 327 $a7.1 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 327 $a8.6 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 327 $aA.2.5 Updating interaction structure and other variables 330 $a"This book is organized in two parts: the first part introduces the reader to all the concepts, tools and references that are required to start conducting research in behavioral computational social science. The methodological reasons for integrating the two approaches are also presented from the individual and separated viewpoints of the two approaches.The second part of the book, presents all the advanced methodological and technical aspects that are relevant for the proposed integration. Several contributions which effectively merge the computational and the behavioral approaches are presented and discussed throughout"--$cProvided by publisher. 330 $a"Provides a unified approach to social research, integrating both agent-based models and behavioral studies.Introduces the reader to all the concepts, tools and references that are required for conducting research in behavioral computational social science"--$cProvided by publisher. 410 0$aWiley series in computational and quantitative social science. 606 $aSocial sciences$xMathematical models 606 $aSocial sciences$xData processing 615 0$aSocial sciences$xMathematical models. 615 0$aSocial sciences$xData processing. 676 $a300.72 686 $aMAT029000$2bisacsh 700 $aBoero$b Riccardo$0901599 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910131482203321 996 $aBehavioral computational social science$92015193 997 $aUNINA