Decentralized systems are ubiquitous in the modern world. Communication systems, sensor networks, power systems and economic systems like markets and auctions are all examples of decentralized systems. Such systems are characterized by the presence of multiple decision-making agents acting on different information. In this talk, I focus on the problem of finding optimal decision-strategies for co-operative agents in a decentralized system. In particular, I consider a decentralized stochastic decision-making problem with multiple decision-makers that share information with each other with a fixed delay. Such decision problems arise in queuing networks, wireless communication networks, distributed control systems, sensing and surveillance systems etc. In spite of initial conjectures as early as 1971, finding the general structure of agents' optimal decision-strategies with delayed information sharing had remained an open problem for 40 years. My research provides a conceptual framework that not only identifies the structure of optimal decision strategies but also provides a sequential decomposition of the optimization problem. Moreover, the methodology developed here is shown to be applicable to a broader class of decentralized decision making problems arising in diverse application domains.
Ashutosh Nayyar received the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology, Delhi, India in 2006. He received the MS degree in Electrical Engineering and Computer Science in 2008, the MS degree in Applied Mathematics in 2011 and the PhD degree in Electrical Engineering and Computer Science in 2011, all from the University of Michigan, Ann Arbor. He worked as a post-doctoral researcher at the University of Illinois at Urbana-Champaign and at the University of California, Berkeley before joining the University of Southern California in 2014. His research focuses on the theory and applications of decentralized decision-making in a wide array of decentralized systems such as: sensing and communication systems, decentralized control systems, cyber-physical systems and electric energy systems.
