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Marco Tomassini


Marco Tomassini

University of Lausanne Switzerland

Marco Tomassini is a professor of Computer Science at the Information Systems Department of the Business and Economics Faculty of the University of Lausanne, Switzerland. He graduated in physical and chemical sciences and got a Doctor's degree in Theoretical Chemistry from the University of Perugia, Italy, working on computer simulations of condensed matter systems. After some years doing research on crystal and molecular physics, he switched to computer science, contributing especially in the fields of parallel computing, heuristics for difficult optimization problems, and cellular automata modeling. His current research interests are centered around game-theoretical models and human behavior in laboratory experiments, and the network dimension of complex socio-economical systems. M. Tomassini has been Program Chair or organizer of several international events and has published more than 250 scientific papers and several authored and edited books in the above fields. In 2010 he was awarded the EvoStarAwardin recognition of outstanding contributions to Evolutionary Computation.


Project:  Game Theory is an important quantitative approach in social and economic sciences. Our line of research has been essentially based on theoretical models and numerical computer simulations but we have recently added an experimental dimension as well as experiments contrast real human behavior with the prescribed theoretical behavior of optimizing rational agents postulated by the theory. The results until now show that, while there is in general qualitative agreement between theory and experiment, the quantitative match is not very good. During my stay at GISC we plan on building on our experimental results to understand people’s patterns of behavior under different realistic conditions. The main idea is thus to make use of significant experimental data to infer by statistics and mathematical models of learning new, less restrained models of how people behave in realistic  conditions. These models could then be fed back into numerical simulations that are much faster and less expensive than experiments with humans. Subsequently, simulations using these new models could then make the task of designing new experiments cheaper and safer by quickly exploring all the relevant alternatives. In addition, by allowing such a comparison of predicted and observed behavior, our project will eventually lead to policy recommendations for public institutions and private corporations which may be useful to improve the cooperativeness of the people they involve.

Stay period: SEP 2015 - FEB 2016