About this product

Product Identifiers

PublisherSAGE Publications, Incorporated

ISBN-101412949645

ISBN-139781412949644

eBay Product ID (ePID)59361575

Product Key Features

Number of Pages112 Pages

LanguageEnglish

Publication NameAgent-Based Models

SubjectGame Theory, Computer Simulation, Research, Statistics

Publication Year2007

TypeTextbook

Subject AreaMathematics, Computers, Social Science

AuthorNigel Gilbert

SeriesQuantitative Applications in the Social Sciences Ser.

FormatPerfect

Dimensions

Item Height0.2 in

Item Weight5 Oz

Item Length8.3 in

Item Width5.4 in

Additional Product Features

Intended AudienceCollege Audience

LCCN2007-014599

Dewey Edition22

Series Volume Number153

IllustratedYes

Dewey Decimal519.3

Table Of ContentSeries Editors IntroductionPrefaceAcknowledgments1. The Idea of Agent-Based Modeling1.1 Agent-Based Modeling1.2 Some Examples1.3 The Features of Agent-Based Modeling1.4 Other Related Modeling Approaches2. Agents, Environments, and Timescales2.1 Agents2.2 Environments2.3 Randomness2.4 Time3. Using Agent-Based Models in Social Science Research3.1 An Example of Developing an Agent-Based Model3.2 Verification: Getting Rid of the Bugs3.3 Validation3.4 Techniques for Validation3.5 Summary4. Designing and Developing Agent-Based Models4.1 Modeling Toolkits, Libraries, Languages, Frameworks, and Environments4.2 Using NetLogo to Build Models4.3 Building the Collectivities Model Step by Step4.4 Planning an Agent-Based Model Project4.5 Reporting Agent-Based Model Research4.6 Summary5. Advances in Agent-Based Modeling5.1 Geographical Information Systems5.2 Learning5.3 Simulating LanguageResourcesGlossaryReferencesIndexAbout the Author

SynopsisAgent-based modeling (ABM) is a technique increasingly used in a broad range of social sciences. It involves building a computational model consisting of "agents," each of which represents an actor in the social world, and an "environment" in which the agents act. Agents are able to interact with each other and are programmed to be pro-active, autonomous and able to perceive their virtual world. The techniques of ABM are derived from artificial intelligence and computer science, but are now being developed independently in research centers throughout the world. In Agent-Based Models, Nigel Gilbert reviews a range of examples of agent-based modeling, describes how to design and build your own models, and considers practical issues such as verification, validation, planning a modeling project, and how to structure a scholarly article reporting the results of agent-based modeling. It includes a glossary, an annotated list of resources, advice on which programming environment to use when creating agent-based models, and a worked, step-by-step example of the development of an ABM. This latest volume in the SAGE Quantitative Applications in the Social Sciences series will have wide appeal in the social sciences, including the disciplines of sociology, economics, social psychology, geography, economic history, science studies, and environmental studies. It is appropriate for graduate students, researchers and academics in these fields, for both those wanting to keep up with new developments in their fields and those who are considering using ABM for their research. Key Features Aimed at readers who are new to ABM Offers a brief, but thorough, treatment of a cutting-edge technique Offers practical advice about how to design and create ABM Includes carefully chosen examples from different disciplines Learn more about "The Little Green Book" - QASS Series Click Here, Agent-based modeling (ABM) is a technique increasingly used in a broad range of social sciences. It involves building a computational model consisting of "agents," each of which represents an actor in the social world, and an "environment" in which the agents act. Agents are able to interact with each other and are programmed to be pro-active, autonomous and able to perceive their virtual world. The techniques of ABM are derived from artificial intelligence and computer science, but are now being developed independently in research centers throughout the world.In Agent-Based Models, Nigel Gilbert reviews a range of examples of agent-based modeling, describes how to design and build your own models, and considers practical issues such as verification, validation, planning a modeling project, and how to structure a scholarly article reporting the results of agent-based modeling. It includes a glossary, an annotated list of resources, advice on which programming environment to use when creating agent-based models, and a worked, step-by-step example of the development of an ABM.This latest volume in the SAGE Quantitative Applications in the Social Sciences series will have wide appeal in the social sciences, including the disciplines of sociology, economics, social psychology, geography, economic history, science studies, and environmental studies. It is appropriate for graduate students, researchers and academics in these fields, for both those wanting to keep up with new developments in their fields and those who are considering using ABM for their research.Key Features Aimed at readers who are new to ABM Offers a brief, but thorough, treatment of a cutting-edge technique Offers practical advice about how to design and create ABM Includes carefully chosen examples from different disciplines Learn more about "The Little Green Book" - QASS Series! Click Here, Agent-based modeling (ABM) is a technique increasingly used in a broad range of social sciences. It involves building a computational model consisting of ?agents, ? each of which represents an actor in the social world, and an "environment" in which the agents act. Agents are able to interact with each other and are programmed to be pro-active, autonomous and able to perceive their virtual world. The techniques of ABM are derived from artificial intelligence and computer science, but are now being developed independently in research centers throughout the world.In Agent-Based Models, Nigel Gilbert reviews a range of examples of agent-based modeling, describes how to design and build your own models, and considers practical issues such as verification, validation, planning a modeling project, and how to structure a scholarly article reporting the results of agent-based modeling. It includes a glossary, an annotated list of resources, advice on which programming environment to use when creating agent-based models, and a worked, step-by-step example of the development of an ABM.This latest volume in the SAGE Quantitative Applications in the Social Sciences series will have wide appeal in the social sciences, including the disciplines of sociology, economics, social psychology, geography, economic history, science studies, and environmental studies. It is appropriate for graduate students, researchers and academics in these fields, for both those wanting to keep up with new developments in their fields and those who are considering using ABM for their research.Key FeaturesAimed at readers who are new to ABMOffers a brief, but thorough, treatment of a cutting-edge techniqueOfferspractical advice about how to design and create ABMIncludes carefully chosen examples from different disciplines, Agent-based modeling (ABM) is a technique increasingly used in a broad range of social sciences. It involves building a computational model consisting of "agents," each of which represents an actor in the social world, and an "environment" in which the agents act. Agents are able to interact with each other and are programmed to be pro-active, autonomous and able to perceive their virtual world. The techniques of ABM are derived from artificial intelligence and computer science, but are now being developed independently in research centers throughout the world. In Agent-Based Models, Nigel Gilbert reviews a range of examples of agent-based modeling, describes how to design and build your own models, and considers practical issues such as verification, validation, planning a modeling project, and how to structure a scholarly article reporting the results of agent-based modeling. It includes a glossary, an annotated list of resources, advice on which programming environment to use when creating agent-based models, and a worked, step-by-step example of the development of an ABM. This latest volume in the SAGE Quantitative Applications in the Social Sciences series will have wide appeal in the social sciences, including the disciplines of sociology, economics, social psychology, geography, economic history, science studies, and environmental studies. It is appropriate for graduate students, researchers and academics in these fields, for both those wanting to keep up with new developments in their fields and those who are considering using ABM for their research. Key Features Aimed at readers who are new to ABM Offers a brief, but thorough, treatment of a cutting-edge technique Offers practica

LC Classification NumberHA29.G527 2008