Simulation for the Social Scientist / Edition 2

by Nigel Gilbert, Klaus Troitzsch, Klaus G. Troitzsch

Overview

Simulation for the Social Scientist is a practical textbook on the techniques of building computer simulations to assist understanding of social and economic issues and problems. This authoritative book details all the common approaches to social simulation, to provide social scientists with an appreciation of the literature and allow those with some programming skills to create their own simulations.

Product Details

ISBN-13:	9780335216000
Publisher:	McGraw-Hill Professional Publishing
Publication date:	02/01/2005
Edition description:	REV
Pages:	312
Product dimensions:	6.00(w) x 8.90(h) x 0.60(d)

About the Author

Nigel Gilbert (United Kingdom) is a member of the Sociology Department at the University of Surrey.

Dr. Klaus G. Troitzsch (Germany) is based at the Universitat Koblenz-Landau.

Table of Contents

	Preface	ix
1	Simulation and social science	1
	What is simulation?	2
	The history of social science simulation	6
	Simulating human societies	9
	Conclusion	12
2	Simulation as a method	14
	The logic of simulation	15
	The stages of simulation-based research	17
	Conclusion	25
3	System dynamics and world models	27
	Software	30
	An example: Hawks, doves and law-abiders	31
	Commentary	42
	World models	43
	Problems and an outlook	48
	Further reading	51
4	Microanalytical simulation models	53
	Methodologies	56
	Software	61
	Examples	62
	Commentary	71
	Further reading	72
5	Queuing models	74
	Characteristics of queuing models	75
	Software	81
	Examples	81
	Commentary	90
	Further reading	90
6	Multilevel simulation models	92
	Some synergetics	94
	Software: MIMOSE	99
	Examples	105
	Commentary	118
	Further reading	119
7	Cellular automata	121
	The Game of Life	123
	Other cellular automata models	125
	Extensions to the basic model	136
	Software	141
	Further reading	157
8	Multi-agent models	158
	Agents and agency	159
	Agent architecture	164
	Examples of multi-agent modelling	168
	Building multi-agent simulations	174
	Further reading	193
9	Learning and evolutionary models	195
	Artificial neural networks	197
	Using artificial neural networks for social simulation	200
	Designing neural networks	205
	Implementation	207
	Genetic algorithms	218
	Further reading	236
Appendix A	Web sites	238
	General	238
	Programs, packages and languages	239
	Electronic journals	241
	System dynamics	241
	Microsimulation	242
	Queuing models	244
	Cellular Automata	245
	Distributed artificial intelligence	246
	Genetic algorithms	247
	Neural networks	248
Appendix B	Linear stability analysis of the hawk-dove-law-abider model	250
Appendix C	Random number generators	254
	References	257
	Author index	266
	Subject index	269

Editorial Reviews

Gilbert (sociology, U. of Surrey) and Troitzsch (social science informatics, U. of Koblenz-Landau, Germany) offer a practical textbook on techniques for building simulations to assist the understanding of social and economics issues. They explain what computer simulation can contribute to the social sciences, which of the many approaches to simulation would be best for a particular research project, and how to design and carry out a simulation and analyze the results. Computer scientists might also benefit from reading what functions social scientists need and what problems they have with existing packages. US distribution by Taylor and Francis. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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