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Workshop on Cognition and Control

Information Acquisition and Utilization Problems
Tara Javidi
Tara Javidi studied electrical engineering at Sharif University of Technology, Tehran, Iran from 1992 to 1996. She received the MS degrees in electrical engineering (systems), and in applied mathematics (stochastics) from the University of Michigan, Ann Arbor, in 1998 and 1999, respectively. She received her Ph.D. in electrical engineering and computer science from the University of Michigan, Ann Arbor, in 2002.
From 2002 to 2004, she was an assistant professor at the Electrical Engineering Department, University of Washington, Seattle. She joined University of California, San Diego, in 2005, where she is currently an associate professor of electrical and computer engineering.
Information Acquisition and Utilization Problems (IAUP) form a class of stochastic decision problems in which a (set of) decision maker(s), by carefully controlling a sequence of actions with uncertain outcomes, dynamically refines the belief about stochastically time-varying (Markovian) parameters of interest in order to best utilize the available resources. Examples arise in patient care, computer vision, spectrum utilization, and joint source--channel coding. A generalization of hidden Markov models and a special case of partially observable Markov models, IAUPs are purely informational problems: the twin-set of actions explicitly corresponding to the joint activities of acquisition (e.g. spectrum sensing) and utilization (e.g. communication of bits) do not affect the underlying stochastic evolution of the environment (the time-varying spectrum) directly. We discuss the connection to filter stability, information utility, mutual information and Extrinsic Jensen--Shannon divergence.
February 21
Reitz Union 346

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