Social Modeling for Multi-agent Systems Gita Sukthankar Department of Computer Science University of Central Florida Orlando, FL
[email protected]
EXTENDED ABSTRACT A key collaboration challenge is making complex ecosystems composed of robots, agents, and humans function together to achieve an overarching task. To do this requires both teamwork and mutual understanding between humans and software agents. As these systems scale up in size, effective data analytics and network science become critical towards understanding and guiding systems operation. My premise is that the same techniques that are useful for studying human social systems are also for studying these semi-artificial systems. In this talk I present two case studies of combining and analyzing human and agent systems in new and innovative ways.
Institute for Simulation and Training. She received an A.B. in psychology from Princeton University and a M.S. and Ph.D. from the Robotics Institute at Carnegie Mellon University. In 2009, Dr. Sukthankar was selected for an Air Force Young Investigator award, the DARPA Computer Science Study Panel, and a NSF CAREER award. Gita Sukthankar’s research focuses on multi-agent systems and computational social models.
REFERENCES [1]
BIOGRAPHIES GITA SUKTHANKAR is an Associate Professor and Charles N. Millican Faculty Fellow in the Department of Electrical Engineering and Computer Science at the University of Central Florida, and an affiliate faculty member at UCF’s
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A. Hajibagheri, K.Lakkaraju, G. Sukthankar, "A holistic approach to link prediction in multiplex networks,", Proceedings of the International Conference on Social Informatics, 2016 E. Davami and G. Sukthankar, “Improving the performnce of mobile phone based crowdsourcing applications," Proceedings of the International Conference on Autonomous Agents, pp. 145-151, May 2015
