Agent Based Computational Sociology
Download Agent Based Computational Sociology PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Agent Based Computational Sociology book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Agent-Based Computational Sociology
Author: Flaminio Squazzoni
language: en
Publisher: John Wiley & Sons
Release Date: 2012-02-27
Most of the intriguing social phenomena of our time, such as international terrorism, social inequality, and urban ethnic segregation, are consequences of complex forms of agent interaction that are difficult to observe methodically and experimentally. This book looks at a new research stream that makes use of advanced computer simulation modelling techniques to spotlight agent interaction that allows us to explain the emergence of social patterns. It presents a method to pursue analytical sociology investigations that look at relevant social mechanisms in various empirical situations, such as markets, urban cities, and organisations. This book: Provides a comprehensive introduction to epistemological, theoretical and methodological features of agent-based modelling in sociology through various discussions and examples. Presents the pros and cons of using agent-based models in sociology. Explores agent-based models in combining quantitative and qualitative aspects, and micro- and macro levels of analysis. Looks at how to pose an agent-based research question, identifying the model building blocks, and how to validate simulation results. Features examples of agent-based models that look at crucial sociology issues. Supported by an accompanying website featuring data sets and code for the models included in the book. Agent-Based Computational Sociology is written in a common sociological language and features examples of models that look at all the traditional explanatory challenges of sociology. Researchers and graduate students involved in the field of agent-based modelling and computer simulation in areas such as social sciences, cognitive sciences and computer sciences will benefit from this book.
Agent-Based Computational Sociology
Author: Flaminio Squazzoni
language: en
Publisher: John Wiley & Sons
Release Date: 2012-04-23
Most of the intriguing social phenomena of our time, such as international terrorism, social inequality, and urban ethnic segregation, are consequences of complex forms of agent interaction that are difficult to observe methodically and experimentally. This book looks at a new research stream that makes use of advanced computer simulation modelling techniques to spotlight agent interaction that allows us to explain the emergence of social patterns. It presents a method to pursue analytical sociology investigations that look at relevant social mechanisms in various empirical situations, such as markets, urban cities, and organisations. This book: Provides a comprehensive introduction to epistemological, theoretical and methodological features of agent-based modelling in sociology through various discussions and examples. Presents the pros and cons of using agent-based models in sociology. Explores agent-based models in combining quantitative and qualitative aspects, and micro- and macro levels of analysis. Looks at how to pose an agent-based research question, identifying the model building blocks, and how to validate simulation results. Features examples of agent-based models that look at crucial sociology issues. Supported by an accompanying website featuring data sets and code for the models included in the book. Agent-Based Computational Sociology is written in a common sociological language and features examples of models that look at all the traditional explanatory challenges of sociology. Researchers and graduate students involved in the field of agent-based modelling and computer simulation in areas such as social sciences, cognitive sciences and computer sciences will benefit from this book.
Agent-based Models and Causal Inference
Explore the issue of causal inference in agent-based computational models in a first-of-it’s-kind volume Agent-based Models and Causal Inference delivers an insightful investigation into the conditions under which different quantitative methods can legitimately hold to be able to establish causal claims. The book compares agent-based computational methods with randomized experiments, instrumental variables, and various types of causal graphs. It goes on to explain why there is no strong argument to believe that observational and experimental methods are qualitatively superior to simulation-based methods in their capacity to contribute to establishing causal claims. Organized in two parts, Agent-based Models and Causal Inference connects the literature from various fields, including causality, social mechanisms, statistical and experimental methods for causal inference, and agent-based computation models to help show that causality means different things within different methods for causal analysis, and that persuasive causal claims can only be built at the intersection of these various methods. Readers will also benefit from the inclusion of: A thorough comparison between agent-based computation models to randomized experiments, instrumental variables, and several types of causal graphs. A compelling argument that observational and experimental methods are not qualitatively superior to simulation-based methods in their ability to establish causal claims Practical discussions of how statistical, experimental and computational methods can be combined to produce reliable causal inferences Perfect for academic social scientists and scholars in the fields of computational social science, philosophy, statistics, experimental design, and ecology, Agent-based Models and Causal Inference will also earn a place in the libraries of PhD students seeking a one-stop reference on the issue of causal inference in agent-based computational models.