Agent-based models

نویسنده

  • Nigel Gilbert
چکیده

Agent-based modeling is a new analytical method for the social sciences, but one that is quickly becoming popular. This short book explains what agent-based modeling is. It also warns of some dangers and describes typical ways of doing agent-based modeling. Finally, it offers a range of examples frommany of the social sciences. This first chapter begins with a brief overview of agent-based modeling before contrasting it with other, perhaps more familiar forms of modeling and describing several examples of current agent-based modeling research. Chapter 2 goes into more detail, considering a range of methodological and theoretical issues and explaining what ‘‘agents’’ are. Chapter 3 dives into the specifics of building agent-based models, reviewing available software platforms and showing step by step how one can build an agent-based models using one of these. Chapter 4 provides some practical advice about designing agent-based models, using them in social science research, and publishing articles based on agent-based modeling. Finally, Chapter 5 discusses the future of agent-based modeling research and where advances are likely to be made. The book concludes with a list of resources useful to agent-based modelers on the Web and in print. Agent-based simulation has become increasingly popular as a modeling approach in the social sciences because it enables one to build models where individual entities and their interactions are directly represented. In comparison with variable-based approaches using structural equations, or system-based approaches using differential equations, agent-based simulation offers the possibility of modeling individual heterogeneity, representing explicitly agents’ decision rules, and situating agents in a geographical or another type of space. It allows modelers to represent in a natural way multiple scales of analysis, the emergence of structures at the macro or societal level from individual action, and various kinds of adaptation and learning, none of which is easy to do with other modeling approaches.

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تاریخ انتشار 2006