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Leader |
LDR
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nam a 00 |
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Control # |
1
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hbl99064408 |
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Control # Id |
3
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GCG |
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Date |
5
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20230301095204.0 |
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Fixed Data |
8
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150720s2008 caua 000 0 eng d |
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LC Card |
10
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$a2007014599 |
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ISBN |
20
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$a9781412949644 (pbk) |
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Obsolete |
39
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$a292369$cTLC |
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Cat. Source |
40
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$aGCG |
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LC Call |
50
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0 |
$aH61$b.G527 2008 |
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ME:Pers Name |
100
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1 |
$aGilbert, Nigel G. |
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Title |
245
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10 |
$aAgent-based models /$cNigel G. Gilbert. |
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Imprint |
260
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$aThousand Oaks, CA :$bSage,$cc2008. |
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Phys Descrpt |
300
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$axiii, 98 p. :$bill. ;$c22 cm |
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Series:Diff |
490
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0 |
$aSage University papers series - Quantitative applications in the social sciences ;vv. 07-153 |
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Note:Bibliog |
504
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$aIncludes bibliographical references and index. |
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Note:Content |
505
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0 |
$a1. The Idea of Agent-Based Modeling -- 1.1 Agent-Based Modeling -- 1.1.1 A Computational Method -- 1.1.2 Experiments -- 1.1.3 Models -- 1.1.4 Agents -- 1.1.5 The Environment -- 1.2 Some Examples -- 1.2.1 Urban Models -- 1.2.2 Opinion Dynamics -- 1.2.3 Consumer Behavior -- 1.2.4 Industrial Networks -- 1.2.5 Supply Chain Management -- 1.2.6 Electricity Markets -- 1.2.7 Participative and Companion Modeling -- 1.3 The Features of Agent-Based Modeling -- 1.3.1 Ontological Correspondence -- 1.3.2 Heterogeneous Agents -- 1.3.3 Representation of the Environment -- 1.3.4 Agent Interactions -- 1.3.5 Bounded Rationality -- 1.3.6 Learning -- 1.4 Other Related Modeling Approaches -- 1.4.1 Microsimulation -- 1.4.2 System Dynamics -- 2. Agents, Environments, and Timescales -- 2.1 Agents -- 2.1.1 Ad-Hoc Programming -- 2.1.2 Production Rule Systems -- 2.1.3 Neural Networks -- 2.2 Environments -- 2.3 Randomness -- 2.4 Time -- 3. Using Agent-Based Models in Social Science Research -- 3.1 An Example of Developing an Agent-Based Model -- 3.1.1 Macro-Level Regularities -- 3.1.2 Micro-Level Behavior -- 3.1.3 Designing a Model -- 3.1.4 Verification -- 3.2 Verification: Getting Rid of the Bugs -- 3.3 Validation -- 3.3.1 Abstract Models -- 3.3.2 Middle Range Models -- 3.3.3 Facsimile Models -- 3.4 Techniques for Validation -- 3.4.1 Comparing Theory and the Model: Sensitivity Analysis -- 3.4.2 Comparing the Model and Empirical Data -- 3.5 Summary -- 4. Designing and Developing Agent-Based Models -- 4.1 Modeling Toolkits, Libraries, Languages, Frameworks, and Environments -- 4.1.1 Repast -- 4.1.2 Mason -- 4.1.3 NetLogo -- 4.1.4 Comparison -- 4.2 Using NetLogo to Build Models -- 4.3 Building the Collectivities Model Step by Step -- 4.3.1 Commentary on the Program -- 4.4 Planning an ABM Project -- 4.5 Reporting Agent-Based Model Research -- 4.6 Summary -- 5. Advances in Agent-Based Modeling -- 5.1 Geographical Information Systems (GIS) -- 5.2 Learning -- 5.2.1 Reinforcement Learning -- 5.2.2 Evolutionary Computation -- 5.3 Simulating Language -- Resources -- Glossary -- References -- Index -- About the Author. |
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Subj:Topical |
650
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0 |
$aSocial sciences$xStatistical methods. |
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Subj:Topical |
650
|
0 |
$aGame theory. |
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Subj:Topical |
650
|
0 |
$aComputer simulation. |
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SE:Ufm Title |
830
|
0 |
$aSage University papers series - Quantitative applications in the social sciences ;$vv. 07-153. |
