Abstract:

This talk shall cover a wide variety of practical applications of Markov decision processes (MDPs). MDPs are used for solving stochastic decision-making problems. The speaker will share his experience of over ten years in developing and simulating Markov decision process models in terms of various applications such as robotics, smart buildings, fault tolerance in satellite attitude control, human intent prediction etc. Key challenges such as computational complexity and scalability issues will also be discussed. Moreover, a glance at the future opportunities related to the research in this domain shall be highlighted.

Speaker Bio :

Dr. Ali Nasir obtained his PhD along with M.Sc. degrees in Electrical Engineering and Aerospace Engineering from the University of Michigan Ann Arbor in USA. He received his B.Sc. in Electrical Engineering from University of Engineering and Technology, Taxila. He is the recipient of Fulbright scholarship for MS leading to PhD. He is currently working on distributed control of multi-agent systems and human intent prediction. His research interests also include Approximate Dynamic programming, fault tolerant control, and nonlinear control and estimation