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This title in other editions

Agent-Based and Individual-Based Modeling: A Practical Introduction

by

Agent-Based and Individual-Based Modeling: A Practical Introduction Cover

 

Synopses & Reviews

Publisher Comments:

Agent-based modeling is a new technique for understanding how the dynamics of biological, social, and other complex systems arise from the characteristics and behaviors of the agents making up these systems. This innovative textbook gives students and scientists the skills to design, implement, and analyze agent-based models. It starts with the fundamentals of modeling and provides an introduction to NetLogo, an easy-to-use, free, and powerful software platform. Nine chapters then each introduce an important modeling concept and show how to implement it using NetLogo. The book goes on to present strategies for finding the right level of model complexity and developing theory for agent behavior, and for analyzing and learning from models.

Agent-Based and Individual-Based Modeling features concise and accessible text, numerous examples, and exercises using small but scientific models. The emphasis throughout is on analysis--such as software testing, theory development, robustness analysis, and understanding full models--and on design issues like optimizing model structure and finding good parameter values.

  • The first hands-on introduction to agent-based modeling, from conceptual design to computer implementation to parameterization and analysis
  • Provides an introduction to NetLogo with nine chapters introducing an important modeling concept and showing how to implement it using NetLogo
  • Filled with examples and exercises, with updates and supplementary materials at http://www.railsback-grimm-abm-book.com/
  • Designed for students and researchers across the biological and social sciences
  • Written by leading practitioners

Leading universities that have adopted this book include:

  • Amherst College
  • Brigham Young University
  • Carnegie Mellon University
  • Cornell University
  • Miami University
  • Northwestern University
  • Old Dominion University
  • Portland State University
  • Rhodes College
  • Susquehanna University
  • University College, Dublin
  • University of Arizona
  • University of British Columbia
  • University of Michigan
  • University of South Florida
  • University of Texas at Austin
  • University of Virginia

Synopsis:

"Knitting together ecology, economics, and social systems, this wonderful book will encourage and enlighten novices and experienced modelers alike. It highlights the importance of patterns at every level of the modeling process, the need for clear explication of assumptions, and the benefits of models composed of discrete entities (agents) which interact, evolve, and mimic reality."--Louis Gross, University of Tennessee, Knoxville

"Railsback and Grimm provide a needed book on how to develop, code, and analyze agent-based models. They so expertly explain the art and science of modeling that even the most modeling-shy beginner will master the skills. Readers will also gain a deep understanding of the increasing importance of agent-based models for interpreting the patterns of nature and human society."--Donald L. DeAngelis, U.S. Geological Survey

"Railsback and Grimm have written a superb introduction to agent-based models. They combine hands-on programming exercises, introductions to some of the core concepts in complex systems, and instruction in model design and analysis. The result is an excellent book that's ideal for both undergraduates and academics."--Scott E. Page, author of Diversity and Complexity

"This exceptional book offers a systematic introduction to the scientific use of agent-based modeling, including the implementation, testing, and validation of models. Until now there was no good textbook available to teach students the theory and practice of agent-based modeling. Railsback and Grimm provide such a text, one that will likely become a classic in the field."--Marco A. Janssen, Arizona State University

"This book is an invaluable guide to agent-based modeling. A significant contribution to the field, it will train the next generation of modelers and teach best practices to existing modelers. Railsback and Grimm have in-depth expertise and experience in developing and teaching agent-based modeling, and are well qualified to write such a book."--Richard Stillman, Bournemouth University

Synopsis:

Agent-based modeling is a new technique for understanding how the dynamics of biological, social, and other complex systems arise from the characteristics and behaviors of the agents making up these systems. This innovative textbook gives students and scientists the skills to design, implement, and analyze agent-based models. It starts with the fundamentals of modeling and provides an introduction to NetLogo, an easy-to-use, free, and powerful software platform. Nine chapters then each introduce an important modeling concept and show how to implement it using NetLogo. The book goes on to present strategies for finding the right level of model complexity and developing theory for agent behavior, and for analyzing and learning from models.

Agent-Based and Individual-Based Modeling features concise and accessible text, numerous examples, and exercises using small but scientific models. The emphasis throughout is on analysis--such as software testing, theory development, robustness analysis, and understanding full models--and on design issues like optimizing model structure and finding good parameter values.

  • The first hands-on introduction to agent-based modeling, from conceptual design to computer implementation to parameterization and analysis
  • Filled with examples and exercises, with updates and supplementary materials at http://www.railsback-grimm-abm-book.com
  • Designed for students and researchers across the biological and social sciences
  • Written by leading practitioners

Leading universities that have adopted this book include:

  • mherst College
  • Brigham Young University
  • Carnegie Mellon University
  • Miami University
  • Northwestern University
  • Old Dominion University
  • Portland State University
  • Rhodes College
  • Susquehanna University
  • University College, Dublin
  • University of Arizona
  • University of South Florida
  • University of Virginia

About the Author

Steven F. Railsback is adjunct professor of mathematics at Humboldt State University and a consulting environmental scientist. Volker Grimm is senior scientist in the Department of Ecological Modeling at the Helmholtz Centre for Environmental Research-UFZ in Leipzig and professor at the University of Potsdam. They are the authors of Individual-Based Modeling and Ecology (Princeton).

Table of Contents

Preface xi

Acknowledgments xvii

Part I: Agent-Based Modeling and NetLogo Basics 1

Chapter 1: Models, Agent-Based Models, and the Modeling Cycle 3

1.1 Introduction, Motivation, and Objectives 3

1.2 What Is a Model? 4

1.3 The Modeling Cycle 7

1.4 What Is Agent-Based Modeling? How Is It Different? 9

1.5 Summary and Conclusions 11

1.6 Exercises 12

Chapter 2: Getting Started with NetLogo 15

2.1 Introduction and Objectives 15

2.2 A Quick Tour of NetLogo 16

2.3 A Demonstration Program: Mushroom Hunt 18

2.4 Summary and Conclusions 29

2.5 Exercises 32

Chapter 3: Describing and Formulating ABMs: The ODD Protocol 35

3.1 Introduction and Objectives 35

3.2 What Is ODD and Why Use It? 36

3.3 T he ODD Protocol 37

3.4 Our First Example: Virtual Corridors of Butterflies 42

3.5 Summary and Conclusions 44

3.6 Exercises 45

Chapter 4: Implementing a First Agent-Based Model 47

4.1 Introduction and Objectives 47

4.2 ODD and NetLogo 47

4.3 Butterfly Hilltopping: From ODD to NetLogo 48

4.4 Comments and the Full Program 55

4.5 Summary and Conclusions 58

4.6 Exercises 59

Chapter 5: From Animations to Science 61

5.1 Introduction and Objectives 61

5.2 Observation of Corridors 62

5.3 Analyzing the Model 67

5.4 Time-Series Results: Adding Plots and File Output 67

5.5 A Real Landscape 69

5.6 Summary and Conclusions 72

5.7 Exercises 72

Chapter 6: Testing Your Program 75

6.1 Introduction and Objectives 75

6.2 Common Kinds of Errors 76

6.3 Techniques for Debugging and Testing NetLogo Programs 79

6.4 Documentation of Tests 89

6.5 An Example and Exercise: The Marriage Model 90

6.6 Summary and Conclusions 92

6.7 Exercises 94

Part II: Model Design Concepts 95

Chapter 7: Introduction to Part II 97

7.1 Objectives of Part II? 97

7.2 Overview 98

Chapter 8: Emergence 101

8.1 Introduction and Objectives 101

8.2 A Model with Less-Emergent Dynamics 102

8.3 Simulation Experiments and BehaviorSpace 103

8.4 A Model with Complex Emergent Dynamics 108

8.5 Summary and Conclusions 113

8.6 Exercises 114

Chapter 9: Observation 115

9.1 Introduction and Objectives 115

9.2 Observing the Model via NetLogo's View 116

9.3 Other Interface Displays 119

9.4 File Output 120

9.5 Behavior Space as an Output Writer 123

9.6 Export Primitives and Menu Commands 124

9.7 Summary and Conclusions 124

9.8 Exercises 125

Chapter 10: Sensing 127

10.1 Introduction and Objectives 127

10.2 Who Knows What: The Scope of Variables 128

10.3 Using Variables of Other Objects 131

10.4 Putting Sensing to Work: The Business Investor Model 132

10.5 Summary and Conclusions 140

10.6 Exercises 141

Chapter 11: Adaptive Behavior and Objectives 143

11.1 Introduction and Objectives 143

11.2 Identifying and Optimizing Alternatives in NetLogo 144

11.3 Adaptive Behavior in the Business Investor Model 148

11.4 Non-optimizing Adaptive Traits: A Satisficing Example 149

11.5 The Objective Function 152

11.6 Summary and Conclusions 153

11.7 Exercises 154

Chapter 12: Prediction 157

12.1 Introduction and Objectives 157

12.2 Example Effects of Prediction: The Business Investor Model's Time Horizon 158

12.3 Implementing and Analyzing Submodels 159

12.4 Analyzing the Investor Utility Function 163

12.5 Modeling Prediction Explicitly 165

12.6 Summary and Conclusions 166

12.7 Exercises 167

Chapter 13: Interaction 169

13.1 Introduction and Objectives 169

13.2 Programming Interaction in NetLogo 170

13.3 The Telemarketer Model 171

13.4 The March of Progress: Global Interaction 175

13.5 Direct Interaction: Mergers in the Telemarketer Model 176

13.6 The Customers Fight Back: Remembering Who Called 179

13.7 Summary and Conclusions 181

13.8 Exercises 181

Chapter 14: Scheduling 183

14.1 Introduction and Objectives 183

14.2 Modeling Time in NetLogo 184

14.3 Summary and Conclusions 192

14.4 Exercises 193

Chapter 15: Stochasticity 195

15.1 Introduction and Objectives 195

15.2 Stochasticity in ABMs 196

15.3 Pseudorandom Number Generation in NetLogo 198

15.4 An Example Stochastic Process: Empirical Model of Behavior 203

15.5 Summary and Conclusions 205

15.6 Exercises 206

Chapter 16: Collectives 209

16.1 Introduction and Objectives 209

16.2 What Are Collectives? 209

16.3 Modeling Collectives in NetLogo 210

16.4 Example: A Wild Dog Model with Packs 212

16.5 Summary and Conclusions 221

16.6 Exercises 222

Part III: Pattern-Oriented Modeling 225

Chapter 17: Introduction to Part III 227

17.1 Toward Structurally Realistic Models 227

17.2 Single and Multiple, Strong and Weak Patterns 228

17.3 Overview of Part III?230

Chapter 18: Patterns for Model Structure 233

18.1 Introduction 233

18.2 Steps in POM to Design Model Structure 234

18.3 Example: Modeling European Beech Forests 235

18.4 Example: Management Accounting and Collusion 239

18.5 Summary and Conclusions 240

18.6 Exercises 241

Chapter 19: Theory Development 243

19.1 Introduction 243

19.2 Theory Development and Strong Inference in the Virtual Laboratory 244

19.3 Examples of Theory Development for ABMs 246

19.4 Exercise Example: Stay or Leave? 249

19.5 Summary and Conclusions 253

19.6 Exercises 254

Chapter 20: Parameterization and Calibration 255

20.1 Introduction and Objectives 255

20.2 Parameterization of ABMs Is Different 256

20.3 Parameterizing Submodels 257

20.4 Calibration Concepts and Strategies 258

20.5 Example: Calibration of the Woodhoopoe Model 264

20.6 Summary and Conclusions 267

20.7 Exercises 268

Part IV: Model Analysis 271

Chapter 21: Introduction to Part IV 273

21.1 Objectives of Part IV?273

21.2 Overview of Part IV?274

Chapter 22: Analyzing and Understanding ABMs 277

22.1 Introduction 277

22.2 Example Analysis: The Segregation Model 278

22.3 Additional Heuristics for Understanding ABMs 283

22.4 Statistics for Understanding 287

22.5 Summary and Conclusions 288

22.6 Exercises 288

Chapter 23: Sensitivity, Uncertainty, and Robustness Analysis 291

23.1 Introduction and Objectives 291

23.2 Sensitivity Analysis 293

23.3 Uncertainty Analysis 297

23.4 Robustness Analysis 302

23.5 Summary and Conclusions 306

23.6 Exercises 307

Chapter 24: Where to Go from Here 309

24.1 Introduction 309

24.2 Keeping Your Momentum: Reimplementation 310

24.3 Your First Model from Scratch 310

24.4 Modeling Agent Behavior 311

24.5 ABM Gadgets 312

24.6 Coping with NetLogo's Limitations 313

24.7 Beyond NetLogo 315

24.8 An Odd Farewell 316

References 317

Index 323

Index of Programming Notes 329

Product Details

ISBN:
9780691136745
Author:
Railsback, Steven F.
Publisher:
Princeton University Press
Author:
Steven F.
Author:
Railsback,
Author:
Grimm, Volker
Author:
Steven F. Railsb
Author:
ack
Subject:
Biology
Subject:
Biological Sciences.
Subject:
Mathematics
Subject:
Biology-General
Subject:
Mathematics-Systems Theory
Edition Description:
Trade paper
Publication Date:
20111131
Binding:
TRADE PAPER
Language:
English
Illustrations:
67 line illus. 6 tables.
Pages:
352
Dimensions:
10 x 8 in

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Computers and Internet » Artificial Intelligence » General
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Science and Mathematics » Mathematics » Systems Theory
Textbooks » General

Agent-Based and Individual-Based Modeling: A Practical Introduction New Trade Paper
0 stars - 0 reviews
$57.25 In Stock
Product details 352 pages Princeton University Press - English 9780691136745 Reviews:
"Synopsis" by , "Knitting together ecology, economics, and social systems, this wonderful book will encourage and enlighten novices and experienced modelers alike. It highlights the importance of patterns at every level of the modeling process, the need for clear explication of assumptions, and the benefits of models composed of discrete entities (agents) which interact, evolve, and mimic reality."--Louis Gross, University of Tennessee, Knoxville

"Railsback and Grimm provide a needed book on how to develop, code, and analyze agent-based models. They so expertly explain the art and science of modeling that even the most modeling-shy beginner will master the skills. Readers will also gain a deep understanding of the increasing importance of agent-based models for interpreting the patterns of nature and human society."--Donald L. DeAngelis, U.S. Geological Survey

"Railsback and Grimm have written a superb introduction to agent-based models. They combine hands-on programming exercises, introductions to some of the core concepts in complex systems, and instruction in model design and analysis. The result is an excellent book that's ideal for both undergraduates and academics."--Scott E. Page, author of Diversity and Complexity

"This exceptional book offers a systematic introduction to the scientific use of agent-based modeling, including the implementation, testing, and validation of models. Until now there was no good textbook available to teach students the theory and practice of agent-based modeling. Railsback and Grimm provide such a text, one that will likely become a classic in the field."--Marco A. Janssen, Arizona State University

"This book is an invaluable guide to agent-based modeling. A significant contribution to the field, it will train the next generation of modelers and teach best practices to existing modelers. Railsback and Grimm have in-depth expertise and experience in developing and teaching agent-based modeling, and are well qualified to write such a book."--Richard Stillman, Bournemouth University

"Synopsis" by , Agent-based modeling is a new technique for understanding how the dynamics of biological, social, and other complex systems arise from the characteristics and behaviors of the agents making up these systems. This innovative textbook gives students and scientists the skills to design, implement, and analyze agent-based models. It starts with the fundamentals of modeling and provides an introduction to NetLogo, an easy-to-use, free, and powerful software platform. Nine chapters then each introduce an important modeling concept and show how to implement it using NetLogo. The book goes on to present strategies for finding the right level of model complexity and developing theory for agent behavior, and for analyzing and learning from models.

Agent-Based and Individual-Based Modeling features concise and accessible text, numerous examples, and exercises using small but scientific models. The emphasis throughout is on analysis--such as software testing, theory development, robustness analysis, and understanding full models--and on design issues like optimizing model structure and finding good parameter values.

  • The first hands-on introduction to agent-based modeling, from conceptual design to computer implementation to parameterization and analysis
  • Filled with examples and exercises, with updates and supplementary materials at http://www.railsback-grimm-abm-book.com
  • Designed for students and researchers across the biological and social sciences
  • Written by leading practitioners

Leading universities that have adopted this book include:

  • mherst College
  • Brigham Young University
  • Carnegie Mellon University
  • Miami University
  • Northwestern University
  • Old Dominion University
  • Portland State University
  • Rhodes College
  • Susquehanna University
  • University College, Dublin
  • University of Arizona
  • University of South Florida
  • University of Virginia

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