Agent-based modeling and simulation (ABMS) is a recent approach to modeling systems comprised of interacting autonomous agents. ABMS is already having far-reaching effects on the way that business and government use computers to support decision-making. Computational advances have made possible a growing number of agent-based applications in a variety of fields at ever-increasing scales. Applications range from using ABMS to model supply chains and logistics systems, to predicting the spread of epidemics and the diffusion of public information, from the identifying factors in the fall of ancient civilizations to understanding contemporary urban conflict, to name a few. This talk, based on North and Macal's book "Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation" (Oxford 2007), describes the foundations of ABM as well as the software toolkits and methods for developing agent models, which range from spreadsheets to enterprise-scale computer systems. I will discuss the relationship between ABMS and traditional modeling techniques, emphasizing the value-added that ABMS provides, along with special challenges pertaining to data and model validation.

Argonne Physics Division Colloquium Schedule