B005KLQYJ0 EBOK by Railsback, Steven F. -- Read -- Imperial Library of Trantor

Index

Title Page Copyright Page Contents Preface Acknowledgments Part I - Agent-Based Modeling and NetLogo Basics

1 - Models, Agent-Based Models, and the Modeling Cycle

1.1 - Introduction, Motivation, and Objectives 1.2 - What is a Model? 1.3 - The Modeling Cycle 1.4 - What is Agent-Based Modeling? How is It Different? 1.5 - Summary and Conclusions 1.6 - Exercises

2 - Getting Started with NetLogo

2.1 - Introduction and Objectives 2.2 - A Quick Tour of NetLogo 2.3 - A Demonstration Program: Mushroom Hunt 2.4 - Summary and Conclusions 2.5 - Exercises

3 - Describing and Formulating ABMs: The Odd Protocol

3.1 - Introduction and Objectives 3.2 - What is Odd and Why Use it? 3.3 - The Odd Protocol 3.4 - Our First Example: Virtual Corridors of Butterflies 3.5 - Summary and Conclusions 3.6 - Exercises

4 - Implementing a First Agent-Based Model

4.1 - Introduction and Objectives 4.2 - Odd and NetLogo 4.3 - Butterfly Hilltopping: From Odd to NetLogo 4.4 - Comments and the Full Program 4.5 - Summary and Conclusions 4.6 - Exercises

5 - From Animations to Science

5.1 - Introduction and Objectives 5.2 - Observation of Corridors 5.3 - Analyzing the Model 5.4 - Time-Series Results: Adding Plots and File Output 5.5 - A Real Landscape 5.6 - Summary and Conclusions 5.7 - Exercises

6 - Testing Your Program

6.1 - Introduction and Objectives 6.2 - Common Kinds of Errors 6.3 - Techniques for Debugging and Testing NetLogo Programs 6.4 - Documentation of Tests 6.5 - An Example and Exercise: The Marriage Model 6.6 - Summary and Conclusions 6.7 - Exercises

Part II - Model Design Concepts

7 - Introduction to Part II

7.1 - Objectives of Part II 7.2 - Overview

8 - Emergence

8.1 - Introduction and Objectives 8.2 - A Model with Less-Emergent Dynamics 8.3 - Simulation Experiments and BehaviorSpace 8.4 - A Model with Complex Emergent Dynamics 8.5 - Summary and Conclusions 8.6 - Exercises

9 - Observation

9.1 - Introduction and Objectives 9.2 - Observing the Model via NetLogo's View 9.3 - Other Interface Displays 9.4 - File Output 9.5 - BehaviorSpace as an Output Writer 9.6 - Export Primitives and Menu Commands 9.7 - Summary and Conclusions 9.8 - Exercises

10 - Sensing

10.1 - Introduction and Objectives 10.2 - Who Knows What: The Scope of Variables 10.3 - Using Variables of Other Objects 10.4 - Putting Sensing to Work: The Business Investor Model 10.5 - Summary and Conclusions 10.6 - Exercises

11 - Adaptive Behavior and Objectives

11.1 - Introduction and Objectives 11.2 - Identifying and Optimizing Alternatives in NetLogo 11.3 - Adaptive Behavior in the Business Investor Model 11.4 - Non-optimizing Adaptive Traits: A Satisficing Example 11.5 - The Objective Function 11.6 - Summary and Conclusions 11.7 - Exercises

12 - Prediction

12.1 - Introduction and Objectives 12.2 - Example Effects of Prediction: The Business Investor Model's Time Horizon 12.3 - Implementing and Analyzing Submodels 12.4 - Analyzing the Investor Utility Function 12.5 - Modeling Prediction Explicitly 12.6 - Summary and Conclusions 12.7 - Exercises

13 - Interaction

13.1 - Introduction and Objectives 13.2 - Programming Interaction in NetLogo 13.3 - The Telemarketer Model 13.4 - The March of Progress: Global Interaction 13.5 - Direct Interaction: Mergers in the Telemarketer Model 13.6 - The Customers Fight Back: Remembering Who Called 13.7 - Summary and Conclusions 13.8 - Exercises

14 - Scheduling

14.1 - Introduction and Objectives 14.2 - Modeling Time in NetLogo 14.3 - Summary and Conclusions 14.4 - Exercises

15 - Stochasticity

15.1 - Introduction and Objectives 15.2 - Stochasticity in ABMs 15.3 - Pseudorandom Number Generation in NetLogo 15.4 - An Example Stochastic Process: Empirical Model of Behavior 15.5 - Summary and Conclusions 15.6 - Exercises

16 - Collectives

16.1 - Introduction and Objectives 16.2 - What are Collectives? 16.3 - Modeling Collectives in NetLogo 16.4 - Example: A Wild Dog Model with Packs 16.5 - Summary and Conclusions 16.6 - Exercises

Part III - Pattern-Oriented Modeling

17 - Introduction to Part III

17.1 - Toward Structurally Realistic Models 17.2 - Single and Multiple, Strong and Weak Patterns 17.3 - Overview of Part III

18 - Patterns for Model Structure

18.1 - Introduction 18.2 - Steps in POM to Design Model Structure 18.3 - Example: Modeling European Beech Forests 18.4 - Example: Management Accounting and Collusion 18.5 - Summary and Conclusions 18.6 - Exercises

19 - Theory Development

19.1 - Introduction 19.2 - Theory Development and Strong Inference in the Virtual Laboratory 19.3 - Examples of Theory Development for ABMs 19.4 - Exercise Example: Stay or Leave? 19.5 - Summary and Conclusions 19.6 - Exercises

20 - Parameterization and Calibration

20.1 - Introduction and Objectives 20.2 - Parameterization of ABMs is Different 20.3 - Parameterizing Submodels 20.4 - Calibration Concepts and Strategies 20.5 - Example: Calibration of the Woodhoopoe Model 20.6 - Summary and Conclusions 20.7 - Exercises

Part IV - Model Analysis

21 - Introduction to Part IV

21.1 - Objectives of Part IV 21.2 - Overview of Part IV

22 - Analyzing and Understanding ABMs

22.1 - Introduction 22.2 - Example Analysis: The Segregation Model 22.3 - Additional Heuristics for Understanding ABMs 22.4 - Statistics for Understanding 22.5 - Summary and Conclusions 22.6 - Exercises

23 - Sensitivity, Uncertainty, and Robustness Analysis

23.1 - Introduction and Objectives 23.2 - Sensitivity Analysis 23.3 - Uncertainty Analysis 23.4 - Robustness Analysis 23.5 - Summary and Conclusions 23.6 - Exercises

24 - Where to Go from Here

24.1 - Introduction 24.2 - Keeping Your Momentum: Reimplementation 24.3 - your First Model from Scratch 24.4 - Modeling Agent Behavior 24.5 - ABM Gadgets 24.6 - Coping with NetLogo's Limitations 24.7 - Beyond NetLogo 24.8 - An Odd Farewell

References Index

Index of Programming Notes

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