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Human decision-makers play a major role in the operation of most real-world systems of today. In most cases, the successful operation of these systems often hinge upon the sound judgment of few individuals. For example, pilots and air traffic controllers continuously make decisions that determine the safety and operation of the National Airspace System (NAS). Even if replacing the humans with automation is conceivable, it will be many decades before the dependence on human decision-making becomes negligible.
Since humans play such a crucial role in characterizing real-world systems, it follows that to make any accurate predictions about system behavior requires a model that is capable of capturing both the human and non-human dynamics of the system. In this talk, I am going to present a game theoric framework to predict the evolution of complex systems with human elements. I will show how this framework is used to predict human decisions in midair aircraft conflicts, aircraft merging and landing and cyber-attacks on smart grids.
Yildiray Yildiz is an associate scientist at NASA Ames Research Center, employed by U.C. Santa Cruz. He received his B Sc. degree from Middle East Technical University in 2002, M Sc. degree from Sabanci University in 2004 and Ph.D. degree from Massachusetts Institute of Technology in 2009.
After completing his Ph.D., Yildiz joined NASA Ames Research Center as a postdoctoral associate and employed by University of California, Santa Cruz. In 2010, he became an associate scientist at the same institution. His research interests lie at the intersection of control theory and applications to aerospace and automotive systems.
Dr. Yildiz is the recipient of a best student paper award and a NASA Group Achievement Award "for outstanding technology development of the CAPIO system at the Vertical Motion Simulator supporting NASA's Green Aviation Initiative." He has been in program committees for several conferences and is a reviewer for several journals. He was a member of the AIAA Guidance, Navigation and Control Technical Committee from 2010 through 2013. His research is supported by Ford Motor Company and NASA Ames Research Center Innovation Funds.