scispace - formally typeset
Open AccessBook

Simulation for the Social Scientist

Reads0
Chats0
TLDR
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, and it will also appeal to computer scientists interested in distributed artificial intelligence, multi-agent systems and agent technologies.
Abstract
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? This 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 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. 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 edition is a chapter on how to use simulation as a tool. A new chapter on multi-agent systems has also been added to support the fact that multi-agent modelling has become the preferred approach to simulation. 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.

read more

Citations
More filters
Journal ArticleDOI

Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review

TL;DR: In this paper, an overview of multi-agent system models of land-use/cover change (MAS/LUCC) is presented, which combine a cellular landscape model with agent-based representations of decisionmaking, integrating the two components through specification of interdependencies and feedbacks between agents and their environment.
Journal ArticleDOI

Tutorial on agent-based modelling and simulation

TL;DR: A brief introduction to ABMS is provided, the main concepts and foundations are illustrated, some recent applications across a variety of disciplines are discussed, and methods and toolkits for developing agent models are identified.
Journal ArticleDOI

FROM FACTORS TO ACTORS: Computational Sociology and Agent-Based Modeling

TL;DR: Agent-based models (ABMs) as mentioned in this paper have been widely used in computational sociology to model social life as interactions among adaptive agents who influence one another in response to the influence they receive, such as diffusion of information, emergence of norms, coordination of conventions or participation in collective action.
Journal ArticleDOI

MASON: A Multiagent Simulation Environment

TL;DR: This paper describes the MASON system, its motivation, and its basic architectural design, and compares MASON to related multi-agent libraries in the public domain, and discusses six applications of the system built over the past year which suggest its breadth of utility.
References
More filters
Book

Adaptation in natural and artificial systems

TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Book

The Art of Computer Programming

TL;DR: The arrangement of this invention provides a strong vibration free hold-down mechanism while avoiding a large pressure drop to the flow of coolant fluid.
Book

Genetic Algorithms + Data Structures = Evolution Programs

TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.
Book

The Sciences of the Artificial

TL;DR: A new edition of Simon's classic work on artificial intelligence as mentioned in this paper adds a chapter that sorts out the current themes and tools for analyzing complexity and complex systems, taking into account important advances in cognitive psychology and the science of design while confirming and extending Simon's basic thesis that a physical symbol system has the necessary and sufficient means for intelligent action.
Book

An Introduction to Genetic Algorithms

TL;DR: An Introduction to Genetic Algorithms focuses in depth on a small set of important and interesting topics -- particularly in machine learning, scientific modeling, and artificial life -- and reviews a broad span of research, including the work of Mitchell and her colleagues.