Simulation for the Social Scientist / Edition 2

Simulation for the Social Scientist / Edition 2

by Nigel Gilbert, Klaus Troitzsch, Klaus G. Troitzsch
     
 

An invaluable guide to the

complex and increasingly

vital study of social

simulation

This is a revised, completely updated edition

of the practical textbook that examines the

techniques of building computer simulations

to assist understanding of social and economic

issues and problems. Interest in social

simulation has been growing

See more details below

Overview

An invaluable guide to the

complex and increasingly

vital study of social

simulation

This is a revised, completely updated edition

of the practical textbook that examines the

techniques of building computer simulations

to assist understanding of social and economic

issues and problems. Interest in social

simulation has been growing rapidly worldwide

as a result of increasingly powerful

hardware capabilities and software programs.

The focus on this area of expertise

is also influenced by a rising interest in the

application of ideas of complexity, evolution,

adaptation, and chaos in the social

sciences.

This authoritative book details all of 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. New for this edition are a

chapter on how to use simulation as a tool,

as well as a chapter on multi-agent systems

to explain why and how multi-agent modeling

has become the preferred approach to

simulation.

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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)

Table of Contents

1Simulation and social science1
2Simulation as a method15
3System dynamics and world models28
4Microanalytical simulation models57
5Queuing models79
6Multilevel simulation models100
7Cellular automata130
8Multi-agent models172
9Developing multi-agent systems199
10Learning and evolutionary models217
AppLinear stability analysis of the dove-hawk-law-abider model267
AppRandom number generators272

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