Artificial Economics: Methods, Models, and Interdisciplinary Links

· Cambridge University Press
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This introductory overview explores the methods, models and interdisciplinary links of artificial economics, a new way of doing economics in which the interactions of artificial economic agents are computationally simulated to study their individual and group behavior patterns. Conceptually and intuitively, and with simple examples, Mercado addresses the differences between the basic assumptions and methods of artificial economics and those of mainstream economics. He goes on to explore various disciplines from which the concepts and methods of artificial economics originate; for example cognitive science, neuroscience, artificial intelligence, evolutionary science and complexity science. Introductory discussions on several controversial issues are offered, such as the application of the concepts of evolution and complexity in economics and the relationship between artificial intelligence and the philosophies of mind. This is one of the first books to fully address artificial economics, emphasizing its interdisciplinary links and presenting in a balanced way its occasionally controversial aspects.

О аутору

Ruben Mercado is a Professor at the Latin American Faculty of Social Sciences and a member of the editorial board for the journal Computational Economics. He holds a Ph.D. in economics from The University of Texas at Austin. His research specializes in computational economics, economic modeling and economic development. In the past, he has taught at the University of Texas at Austin, Bryn Mawr College, the Technological and Higher Studies Institute of Monterrey, and the Universities of Buenos Aires, Quilmes and San Martín. He has also been a Senior Economist at the United Nations Development Program, a Chair for the Study of Western Hemispheric Trade at the Lozano Long Institute of Latin American Studies, and a consultant for the World Bank and the Inter-American Development Bank. He is a co-author of the pioneering textbook Computational Economics (2006).

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