18-22 September 2017
460€, including School Registration and the attendance, teaching material, coffee breaks and lunches. It doesn’t comprise the accommodation. It is possible the participation to single days. The fee for one single day is 160€, including coffee breaks, lunch and teaching material.
The past few years have seen a growing popularity and maturity of collective intelligence research, enabled by advances in information technology and complex systems sciences. Collective intelligence is defined as a shared or group intelligence emerging from the collaboration, collective efforts, and competition of many agents (human or artifacts). The discipline intrinsically grows in a cross-disciplinary research, involving computer science, cognitive science, political science, economics, organization theory, sociobiology, crowd and network sciences. Moreover, big-data research and applications create new opportunity to develop the design of new perspectives for the growth of collective intelligence towards many complex systems and organizations. The main purpose of the School is to enable participants to the most relevant issues and tools supporting new research and application scenarios involving collective intelligence, focusing on the main topics of crowds (from crowdsourcing to crowd management), big-data (large and complex data sets coming from distributed sources to be dealt with innovative data processing application software), and community resilience (sustained ability of a community to utilize available resources to respond to, withstand, and recover from adverse situations).
Exam The organization ofthe courses includes presentations, discussions and contributions in a cross-disciplinary environment, and will also propose research challenges and open issues, as well as concrete case studies related to research and application projects. Participantswill be asked to actively contribute in the discussions andPhDstudentswill be required to develop a final project proposing a novel integrated research or application proposal exploiting the knowledge and information acquired throughout the courses. Contents covered The program will consist of a total of 5 sessions, as follows:
Stefania Bandini, Department of Computer Science, Systems and Communication, University of Milano-Bicocca — Matteo Manera, Department of Economics, Management and Statistics, University of Milano-Bicocca — Mario Mezzanzanica, Department of Statistics and Quantitative Methods, University of Milano-Bicocca — Katsuhiro Nishinari, Research Center of Advanced Science and Technology, The University of Tokyo
Villa del Grumello - Lake Como School of Advanced Studies, Como (Italy) Villa del Grumello
September 10, 2017 Registration
Andrea Gorrini, Organization Chair: firstname.lastname@example.org