Simulation for the Social Scientist

by Nigel Gilbert, Klaus G Troitzsch

Interest in social simulation has been growing rapidly worldwide 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. 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. New for this . A new chapter on designing multi-agent systems, to support the fact that multi-agent modelling has become the most common approach to simulation. New examples and guides to current software. Updated throughout to take new approaches into account. The book is an essential tool for social scientists in a wide range of fields, particularly 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

309 pages, Paperback

First published April 1, 1999

Reviews

[Marco · Rating 5 out of 5]

An introduction to computer simulation techniques that can be useful for social scientific research. The authors select some well-established methods and present their core concepts, relevant design choices, application examples and a bibliography for further learning about that approach. While some of the specific models and approaches no longer belong to the state of the art, that is expected after more than ten years of the book's publication, and the general descriptions are still relevant.

[Jānis · Rating 4 out of 5]

Grāmata par simulācijām. Sākot no primitīviem simulāciju mikromoduļiem un šūnu automātiem līdz pat mums mūsdienās tik ļoti interesantajiem neironu tīkliem un ģenētiskajiem algoritmiem.

Es šo nosauktu par ievadu simulāciju teorijā, kas var pavilkt cilvēku vairāk domāt arī par mašīnmācīšanos.

Grāmata nav jauna, bet ļoti labi parāda to, ka jau pirms 60 gadiem cilvēki domāja kā paredzēt nākotni un kā iemācīt datoru domāt kā cilvēkam.

[Mike Peleah · Rating 4 out of 5]

A good intro to to computer simulation techniques for social scientist. It provides both a broad discussion of modelling methods (in the first chapters) and step-by-step guidance in creating multi-agent models (in the last chapters). Good classic reading. Caveat--it is already 15 years old, and there was progress in this area.

[Nick · Rating 3 out of 5]

Not bad, just a little too dated to be useful for more than summary information.

[Ash Moran · Rating 4 out of 5]

This is a nice straightforward read which covers a surprising amount of ground for a book this size. There's a brief introduction and analysis of system dynamics, microanalytical and multilevel modelling, cellular automata, agent based modelling and genetic algorithms. The examples do a good job of showing the strengths and weaknesses of each approach. I was only interested in learning about agent-based modelling (called multi-agent modelling here), but I was pleasantly surprised to come away with a much broader understanding of how people have tried to model social situations.

[Matt Jans · Rating 5 out of 5]

A really easy read, though I didn't delve into the detailed chapters on simulations...just picked this up on a whim so I haven't used it for a specific project. Need to go back and read chapter on "Stages of simulation research"

[Nikos Bar · Rating 4 out of 5]

This excellent book helped me to accomplish a part of my dissertation. Still remains one of the best introduction books for the social scientists.