The holy-grail of computational social science is to understand how societies behave as a collective, knowing how individuals interact with each-other. Conversely, if all we know is how societies behave collectively (as happens all too often in micro-biology) is there anything we can say about how individuals interact with each-other ? In this talk I will describe how to use massive multi-agent computer simulations to establish a reversible link between individual and collective behavior in large communities. The individual behavior of agents will be modeled by means of a well defined social dilemma of cooperation. Agents will interact along the links of a complex, adaptive social network that co-evolves with individual behavior. I will show that adaptive social networks act to change the dilemma that individuals engage on, revealing a very different behavior at a global level. The fact that this computational link between individual and collective behavior is reversible, proves its usefulness across different disciplines of science.
Jorge Pacheco is Professor of Mathematics at the University of Minho and also a member of the Centre of Molecular and Environmental Biology at the same University. Graduated in Physics in Coimbra, and with a PhD in Theoretical Physics at the Niels Bohr Institute, in Copenhagen. He is carrying out research in a variety of topics, ranging from quantum many-body physics to the mathematical & computational description of evolutionary processes such as cancer, evolution of cooperation, urban development & complexity and complex networks. His interest in environmental problems led him to investigate, more recently, how one should optimize governance in connection to climate change, as well as how to reduce our carbon footprint when installing massive parallel computational infrastructures. A survey of publications can be found in google scholar: http://scholar.google.com/citations?user=3YDAC58AAAAJ&hl=en
Francisco João Duarte Cordeiro Correia dos Santos