Rob Axtell has pioneered the application of agent-based computation to the social sciences in general and economics in particular. His 1996 book with Joshua Epstein, "Growing Artificial Societies: Social Science from the Bottom Up," (MIT Press) introduced the Sugarscape model. Since then his research has appeared in "Science" and the "Proceedings of the National Academy of Sciences, USA," as well as in disciplinary journals. He is Senior Fellow in the Economic Studies Program at the Brookings Institution in Washington, D.C., and an External Faculty member of the Santa Fe Institute. He is currently working on a new book, "Artificial Economies of Adaptive Agents: The Multi-Agent Systems Approach to Positive Economics."

Abstract for Rob Axtell's keynote:

Three gross empirical features of firms are used to argue that reigning economic conceptions of the firm are wholly inadequate. First, the extremely skew distribution of firm sizes in modern industrial countries means simultaneously that (a) no 'representative' firm a la Alfred Marshall exists, (b) industries cannot be understood in isolation, and (c) extant theories of optimal firm size are either empirically vacuous or false, as first argued by Herbert Simon. Second, fluctuations in firm sizes--i.e., growth rate distributions--are sufficiently 'heavy-tailed' that (a) conventional central limit theorem-type arguments concerning log growth rates are not valid, and (b) firm dynamics are intrinsically 'turbulent' suggesting that agent-level fixed points (e.g., Nash equilibria) are irrelevant. Third, and most obviously, firms are multi-agent systems, a feature abstracted away in the neoclassical theory of the firm, and dealt with unsatisfactorily in game theoretic framings of firm structure. By contrast, a model in which heterogeneous, boundedly rational agents interact locally out of equilibrium through social networks, yielding temporary coalitions involving productive activities, closely reproduces these gross empirical features of firms. Some analytical progress in understanding this inherently dynamic model has been achieved via multi-level methods. However, most of the results obtained to date have been produced by agent-based computational means.

Albert-László Barabási is the Emil T. Hofman Professor of Physics at University of Notre Dame. Born in Transylvania, and educated in Bucharest and Budapest, he received a Ph.D. in physics in 1994 from Boston University. After spending a year at IBM T.J. Watson Research Center he joined Notre Dame in 1995. His research has lead to the discovery and understanding of scale-free networks, capturing the structure of many complex networks in technology and nature, from the World Wide Web to the cell. His current research focuses on applying the concepts developed by his group for characterizing the topology of the www and the Internet to uncovering the structural and topological properties of complex metabolic and genetic networks. He is a Fellow of the American Physical Society and an external member of the Hungarian Academy of Sciences. His recent general audience book entitled Linked: The New Science of Networks (Perseus, 2002) is currently available on ten languages. For more information see http://www.nd.edu/~alb.

Abstract for Albert-László Barabási's keynote: