Simulation for the Social Scientist

by Gilbert, G. Nigel; Troitzsch, Klaus G.

• ISBN13: 9780335197446
• ISBN10: 0335197442
• Format: Paperback
• Copyright: 1999-01-01
• Publisher: Open Univ Pr

Summary

What can computer simulation contribute to the social sciences?* Which of the many approaches to simulation would be best for my social science project?* How do I design, carry out and analyse the results from a computer simulation?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.Interest in social simulation has been growing very rapidly world-wide as a result of increasingly powerful hardware and software and also a rising interest in the application of ideas of complexity, evolution, adaptation and chaos in the social sciences. This authoritative book outlines all the common approaches to social simulation at a level of detail which will give social scientists an appreciation of the literature and allow those with some programming skills to create their own simulations.Social scientists in a wide range of fields will find this book an essential tool for research, particularly in sociology, economics, anthropology, geography, organizational theory, political science, social policy, cognitive psychology and cognitive science. It will also appeal to computer scientists interested in distributed artificial intelligence, multi-agent systems and agent technologies.

Author Biography

Nigel Gilbert is Professor of Sociology at the University of Surrey Klaus G. Troitzsch is Professor of Social Science Informatics at the University of Koblenz-Landau, Germany

Table of Contents

Preface	ix
Simulation and social science	1	(13)
What is simulation?	2	(4)
The history of social science simulation	6	(3)
Simulating human societies	9	(3)
Conclusion	12	(2)
Simulation as a method	14	(13)
The logic of simulation	15	(2)
The stages of simulation-based research	17	(8)
Conclusion	25	(2)
System dynamics and world models	27	(26)
Software	30	(1)
An example: Hawks, doves and law-abiders	31	(11)
Commentary	42	(1)
World models	43	(5)
Problems and an outlook	48	(3)
Further reading	51	(2)
Microanalytical simulation models	53	(21)
Methodologies	56	(5)
Software	61	(1)
Examples	62	(9)
Commentary	71	(1)
Further reading	72	(2)
Queuing models	74	(18)
Characteristics of queuing models	75	(6)
Software	81	(1)
Examples	81	(9)
Commentary	90	(1)
Further reading	90	(2)
Multilevel simulation models	92	(29)
Some synergetics	94	(5)
Software: MIMOSE	99	(6)
Examples	105	(13)
Commentary	118	(1)
Further reading	119	(2)
Cellular automata	121	(37)
The Game of Life	123	(2)
Other cellular automata models	125	(11)
Extensions to the basic model	136	(5)
Software	141	(16)
Further reading	157	(1)
Multi-agent models	158	(37)
Agents and agency	159	(5)
Agent architecture	164	(4)
Examples of multi-agent modelling	168	(6)
Building multi-agent simulations	174	(19)
Further reading	193	(2)
Learning and evolutionary models	195	(43)
Artificial neural networks	197	(3)
Using artificial neural networks for social simulation	200	(5)
Designing neural networks	205	(2)
Implementation	207	(11)
Genetic algorithms	218	(18)
Further reading	236	(2)
Appendix A Web sites	238	(12)
General	238	(1)
Programs, packages and languages	239	(2)
Electronic journals	241	(1)
System dynamics	241	(1)
Microsimulation	242	(2)
Queuing models	244	(1)
Cellular Automata	245	(1)
Distributed artificial intelligence	246	(1)
Genetic algorithms	247	(1)
Neural networks	248	(2)
Appendix B Linear stability analysis of the hawk--dove--lawabider model	250	(4)
Appendix C Random number generators	254	(3)
References	257	(9)
Author index	266	(3)
Subject index	269