Managing Business Complexity Discovering

Agent-based modeling and simulation (ABMS), a way to simulate a large number of choices by individual actors, is one of the most exciting practical developments in business modeling since the invention of relational databases. It represents a new way to understand data and generate informationthat has never been available before--a way for businesses to view the future and to understand and anticipate the likely effects of their decisions on their markets and industries. It thus promises to have far-reaching effects on the way that businesses in many areas use computers to supportpractical decision-making. Managing Business Complexity is the first complete business-oriented agent-based modeling and simulation resource. It has three purposes: first, to teach readers how to think about ABMS, that is, about agents and their interactions; second, to teach readers how to explain the features andadvantages of ABMS to other people and third, to teach readers how to actually implement ABMS by building agent-based simulations. It is intended to be a complete ABMS resource, accessible to readers who haven't had any previous experience in building agent-based simulations, or any other kinds ofmodels, for that matter. It is also a collection of ABMS business applications resources, all assembled in one place for the first time. In short, Managing Business Complexity addresses who needs ABMS and why, where and when ABMS can be applied to the everyday business problems that surround us, andhow specifically to build these powerful agent-based models.

Michael J. North, MBA, Ph.D., is the Deputy Director of the Center for Complex Adaptive Agent Systems Simulation within the Decision and Information Sciences Division of Argonne and the University of Chicago.
Charles M. Macal, Ph.D., P.E., is the Director of the Center for Complex Adaptive Agent Systems Simulation within the Decision and Information Sciences Division of Argonne National Laboratory

The Challenge	p. 3
Why This Book?	p. 3
The Who, What, Where, When. Why, and How of Agents	p. 3
Why Agent-Based Modeling and Simulation Is Needed Now	p. 4
The Foundation of ABMS	p. 5
Why ABMS Is Useful, Usable, and Used	p. 6
How ABMS Works: An Overview	p. 8
Incremental Discovery, Design, and Development	p. 8
How This Book Is Organized	p. 8
Case Studies	p. 9
Note	p. 9
References	p. 9
The ABMS Paradigm	p. 11
Parts Make the Whole	p. 11
The Two Fundamental Types of Models	p. 11
Nondeterminism	p. 13
The Cycle of Innovation	p. 14
Other Angles on Nondeterminism	p. 16
Choosing Behaviors to Model	p. 17
The Spectrum of Model Uses	p. 18
Discovering That the Whole Is Greater Than the Parts	p. 22
Summary	p. 22
Note	p. 23
References	p. 23
Agents Up Close	p. 24
Agents: An Overview	p. 24
Agent Attributes	p. 24
Agent Behaviors	p. 27
Simple Agents or Proto-Agents	p. 27
Complex Agents	p. 31
A Market Example	p. 41
Discover, Design, and Develop	p. 43
Notes	p. 43
References	p. 43
The Roots of ABMS	p. 45
ABMS in Context	p. 45
Historical Roots	p. 45
Complexity Science	p. 46
The Diffusion of ABMS	p. 55
Plectics Redux	p. 56
References	p. 56
The Role of ABMS	p. 59
The Big Picture of Modeling and Simulation for Business Applications	p. 60
A Supply Chain Example	p. 63
A Survey of Modeling Approaches	p. 66
When to Use Agents?	p. 93
Blended Modeling Approaches	p. 93
Summary	p. 94
Note	p. 95
References	p. 95
Discovering Agents and Agent Behaviors	p. 97
Agents Are What They Do	p. 97
Social Agents	p. 97
Examples of Behavioral Theories	p. 97
Agent Diversity	p. 101
Other Agents	p. 101
Multi-Agent Systems	p. 101
Artificial Intelligence	p. 102
Discovering Agents	p. 102
Discovering Agent Behaviors	p. 102
A Market Example	p. 112
Acting Up	p. 114
References	p. 114
Office ABMS	p. 116
Progressive Development	p. 116
Prototyping	p. 116
ABMS Environments	p. 117
The Four Model Growth Paths	p. 117
Leveraging Change	p. 118
Returning to the Questions	p. 121
Office ABMS Architectures	p. 122
The Office ABMS Continuum	p. 123
Examples	p. 126
Back at the Office	p. 128
Notes	p. 128
References	p. 128
How to Do Desktop ABMS	p. 130
ABMS on the Desktop	p. 130
Agent Spreadsheets	p. 130
Dedicated ABMS Prototyping Environments	p. 161
A Market Example	p. 171
Summary	p. 182
Notes	p. 182
References	p. 182
How to Do Participatory ABMS	p. 183
Live and In Person!	p. 183
The Start of It All	p. 183
Strengths and Weaknesses	p. 184
Developing Strong Minds	p. 186
Turning Over Rocks	p. 187
Details, Details, Details,	p. 187
A Market Example	p. 190
Summary	p. 194
Note	p. 194
References	p. 194
How to Do Large-Scale ABMS	p. 195
From Desktops on Up	p. 195
Features Galore!	p. 195
Current Toolkits	p. 206
The Large-Scale Modeling Life Cycle	p. 209
Designing Large-Scale Models for Use	p. 210
Agent Patterns and Antipatterns	p. 215
Examples	p. 217
Summary	p. 219
Notes	p. 219
References	p. 219
ABMS Verification and Validation	p. 221
V&V Overview	p. 221
Verification	p. 222
Validation	p. 226
Related Aspects of V&V	p. 231
Summary	p. 233
References	p. 233
A Visual Approach to Data Collection and Cleaning	p. 235
Tasty Morsels	p. 235
The Fact Food Pyramid	p. 235
A Model Diet	p. 239
Marshmallows and Campfire Stories	p. 239
Cooking Times Vary	p. 240
Data Quality	p. 241
A Recipe for Success	p. 248
Dinner Is Served	p. 253
A Market Example	p. 258
Summary	p. 259
References	p. 260
Understanding and Presenting ABMS Results	p. 261
Analyzing ABMS Results	p. 261
Presenting ABMS Results	p. 278
Seven Steps	p. 282
Notes	p. 282
References	p. 282
ABMS Project Management	p. 283
The ABMS Business Function	p. 283
The Fundamentals	p. 283
Project Goals	p. 284
Stopping Mission Creep	p. 284
Champions	p. 285
The Domain Skills Pyramid	p. 285
ABMS Project Structures	p. 286
The ABMS Business Process	p. 292
Growing Up	p. 296
References	p. 297
Rising to the Challenge	p. 298
The Who, What, Where, When, Why, and How of Agents	p. 298
Useful, Usable, and Used	p. 299
Index	p. 303
Table of Contents provided by Ingram. All Rights Reserved.

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Managing Business Complexity Discovering Strategic Solutions with Agent-Based Modeling and Simulation

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