000			06333cam a2200601 i 4500
001			915311978
003			OCoLC
005			20250128170516.0
006			m o d
007			cr |||||||||||
008			150803s2015 enk ob 001 0 eng
019			_a914355368
020			_a9781119106159 (epub)
020			_a111910615X (epub)
020			_a9781119106166 (pdf)
020			_a1119106168 (pdf)
020			_z9781118657300 (hardback)
020			_a9781119106173
020			_a1119106176
035			_a(OCoLC)915311978 _z(OCoLC)914355368
040			_aDLC _beng _erda _cDLC _dN$T _dIDEBK _dUIU _dYDXCP _dOCLCF _dEBLCP _dCDX _dOCLCO _dDEBSZ _dOCLCQ
042			_apcc
050	0	0	_aH61.25
072		7	_aSOC _x041000 _2bisacsh
072		7	_aSOC _x023000 _2bisacsh
100	1		_aBoero, Riccardo. _0http://id.loc.gov/authorities/names/no2010079222
245	1	0	_aBehavioral computational social science / _cRiccardo Boero
264		1	_aChichester, West Sussex, UK : _bWiley, _c2015
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aWiley series in computational and quantitative social science
506			_aAvailable to OhioLINK libraries
520			_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
520			_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
504			_aIncludes bibliographical references and index
505	0		_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
505	8		_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
505	8		_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
505	8		_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
505	8		_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
650		0	_aSocial sciences _xMathematical models. _0http://id.loc.gov/authorities/subjects/sh2008111800 _934284
650		0	_aSocial sciences _xData processing. _0http://id.loc.gov/authorities/subjects/sh85124007
655		4	_aElectronic books _92032
710	2		_aOhio Library and Information Network. _0http://id.loc.gov/authorities/names/no95058981
776	0	8	_iPrint version: _aBoero, Riccardo. _tBehavioral computational social science _dHoboken : Wiley, 2015 _z9781118657300 _w(DLC) 2015017761
830		0	_aWiley series in computational and quantitative social science. _0http://id.loc.gov/authorities/names/no2013016753
856	4	0	_3OhioLINK _zConnect to resource _uhttps://rave.ohiolink.edu/ebooks/ebc2/9781119106173
856	4	0	_3Wiley Online Library _zConnect to resource _uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781119106173
856	4	0	_3Wiley Online Library _zConnect to resource (off-campus) _uhttps://go.ohiolink.edu/goto?url=https://onlinelibrary.wiley.com/doi/book/10.1002/9781119106173
999			_c200463743 _d81955