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KI-Net Conference Announcement
Modeling and Control in Social DynamicsOct 6 - 9, 2014Department of Mathematics, RU-Camden |
ABSTRACTThere is an increasing interest in models of “social dynamics” in a number of different fields, where “active” agents interact through rules which are motivated by “social” features. This leads to “self-organization”, i.e. the emergence of complicated yet often times very efficient group configurations. Examples are found in different disciplines: animal groups in biology (e.g. murmuration of starlings), crowd dynamics (e.g. zipper effect at bottlenecks) and social networks (e.g. centrality of leaders). Even if specific examples vary with the specific features of interacting agents, general mathematical frameworks capture the relevant mechanisms of self-organization. Within the broad perspective, the meeting will focuson systems reproducing consensus, flocking and alignment phenomena and on their control. GOALSThe goal is to provide a platform for collaboration between mathematicians and experts studying self-organized group behavior in the context of different disciplines --- economics, sociology, business, psychology, etc., who are interested in novel modeling, analysis and simulations of social dynamics. In particular, invited talks at this meeting aim at: 1. Providing a wide panorama of the available mathematical models for social dynamics; 2. Presenting a number of problems from social sciences and economics, presented by expert in the fields, which are amenable of and advanced mathematical modeling; 3. Identify specific research areas of interests, where the need of modeling is still open or need to reach next step.
REGISTRATION CLOSEDORGANIZERS |
CONFIRMED PARTICIPANTSFUNDINGA limited amount of travel and local lodging is available for researchers in the early stages of their career who want to attend the full program, especially for graduate students and post-doctoral fellows. INFORMATION FOR PARTICIPANTSDepartment of Mathematics, RU-Camden (RU-Camden) Email: mcsd14@cscamm.umd.edu ACKNOWLEDGMENTFunding provided by the NSF through the KI-net Grant. |