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Simulation for the Social Scientist

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ISBN-10: 0335216005

ISBN-13: 9780335216000

Edition: 2nd 2005 (Revised)

Authors: Nigel Gilbert, Klaus G. Troitzsch

List price: $53.00
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This text gives advice on techniques for building computer simulations to assist understanding of social and ergonomic issues and problems.
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Book details

List price: $53.00
Edition: 2nd
Copyright year: 2005
Publisher: McGraw-Hill Education
Publication date: 2/1/2005
Binding: Paperback
Pages: 312
Size: 5.75" wide x 8.75" long x 0.75" tall
Weight: 1.100
Language: English

Nigel Gilbert read for a first degree in Engineering, intending to go into the computer industry. However, he was lured into sociology and obtained his doctorate on the sociology of scientific knowledge from the University of Cambridge, under the supervision of Michael Mulkay. His research and teaching interests have reflected his continuing interest in both sociology and computer science (and engineering more widely). His main research interests are processual theories of social phenomena, the development of computational sociology and the methodology of computer simulation, especially agent-based modelling. He is Director of the Centre for Research in Social Simulation. He is also…    

Simulation and social science
What is simulation?
The history of social science simulation
Simulating human societies
Simulation as a method
The logic of simulation
The stages of simulation-based research
System dynamics and world models
An example: doves, hawks and law-abiders
World models
Problems and an outlook
Further reading
Microanalytical simulation models
Further reading
Queuing models
Characteristics of queuing models
Further reading
Multilevel simulation models
Some synergetics
Software: MIMOSE
Further reading
Cellular automata
The Game of Life
Other cellular automata models
Extensions to the basic model
Further reading
Multi-agent models
Agents and agency
Agent architecture
Building multi-agent simulations
Examples of multi-agent modelling
Further reading
Developing multi-agent systems
Making a start
From theory to model
Adding dynamics
Cognitive models
The user interface
Unit tests
Using multi-agent simulations
Further reading
Learning and evolutionary models
Artificial neural networks
Using artificial neural networks for social simulation
Designing neural networks
Evolutionary computation
Further reading
Web sites
Programs, packages and languages
Electronic journals
System dynamics
Queuing models
Cellular automata
Multi-agent systems
Neural networks
Evolutionary computation
Linear stability analysis of the dove-hawk-law-abider model
Random number generators
Author index
Subject index