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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 copyrighted by Book News, Inc., Portland, OR

Tabla de contenidos provista por Syndetics

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

Notas de autor provistas por Syndetics

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