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New book applies agent-based modeling to business decisions


A new book, Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation, has been referred to as a must read for anyone considering applications of agent-based modeling for solving real world problems. Authors of the book are experts Charles Macal and Michael North of the U.S. Department of Energy’s Argonne National Laboratory.

Managing Business Complexity brings recent discoveries in decision science to bear on the business world. This book is the first complete agent-based modeling and simulation resource targeted for business and government audiences. It represents new ways to understand data and generate information, providing organizations a view of the future and the ability to anticipate the likely effects of their decisions.

Agent-based modeling has applications in determining social network effects, workforce administration, portfolio management and consumer behavior, and will have profound impacts on the way computers support decision making. It provides a method for researchers and business managers to visualize the ways in which a large number of individual actors make decisions.

These models comprise many discrete self-determining rule-based programs located within larger networks. Therefore, even though each individual program, or “agent,” bases its actions only on its own inputs, those actions help to determine the inputs, and therefore the actions, of other nearby agents. The resulting behavioral complexity of these networks closely represents the complicated processes and consequences of individual and organizational decision-making.


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