Invited talk by Marco Tomassini
Cooperation and coordination are notoriously difficult goals to achieve. Using basic evolutionary game theory, it can be shown that cooperation is typically doomed, while coordination on inferior Pareto equilibria is commonplace. However, these results are based on mixing populations in which interactions may happen between any pair or group of agents. In this talk it will be shown that, if one takes into account the typical social networks structures that permeates society, the prospects are less gloomy and socially efficient steady states may be achieved.
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 obtained a Doctorate in theoretical chemistry from the University of Perugia, Italy, working on computer simulations of condensed matter systems. After some years in crystal and molecular physics research, he switched to computer science, with particular interest in the fields of parallel computing and cellular automata modeling. His current research interests are centered around the application of biological ideas to artificial systems and the network dimension of complex systems. He is active in evolutionary computation, especially spatially structured systems, genetic programming, and the structure of hard combinatorial search spaces. He is also active in evolutionary games on networks and the evolution of coordination and cooperation, including the dynamical properties of networked complex systems. He has been Program Chair of several international events and has published more than 230 scientific papers and several authored and edited books in these fields.
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Invited talk by Marco Tomassini
Cooperation and coordination are notoriously difficult goals to achieve. Using basic evolutionary game theory, it can be shown that cooperation is typically doomed, while coordination on inferior Pareto equilibria is commonplace. However, these results are based on mixing populations in which interactions may happen between any pair or group of agents. In this talk it will be shown that, if one takes into account the typical social networks structures that permeates society, the prospects are less gloomy and socially efficient steady states may be achieved.
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 obtained a Doctorate in theoretical chemistry from the University of Perugia, Italy, working on computer simulations of condensed matter systems. After some years in crystal and molecular physics research, he switched to computer science, with particular interest in the fields of parallel computing and cellular automata modeling. His current research interests are centered around the application of biological ideas to artificial systems and the network dimension of complex systems. He is active in evolutionary computation, especially spatially structured systems, genetic programming, and the structure of hard combinatorial search spaces. He is also active in evolutionary games on networks and the evolution of coordination and cooperation, including the dynamical properties of networked complex systems. He has been Program Chair of several international events and has published more than 230 scientific papers and several authored and edited books in these fields.