This course explores modern reasoning techniques for the extraction of information from noisy data sources, for the integration of multiple information streams, and for decision-making in the presence of uncertainty. While this course will investigate these techniques often in the context of physical sensor applications and robotics, they are also applicable in a wide range of other fields including mobile networking, data mining, and control of physical processes.
Many of the techniques covered in this course are based on probabilities and knowledge of basic statistics is useful. Prerequisites for this course are either Artificial Intelligence (CSE 5361), Robotics (CSE 5364), an advanced statistics course, or consent of instructor. In addition, experience with programming in C or C++ will be useful to perform assignments and projects.
This course does not have a dedicated textbook.
Readings will consist of chapters taken from a variety of books and papers from technical conferences and journals. Course materials will be available from the instructor or electronically on the course page.
There is a course web page at http://www-cse.uta.edu/
huber/cse6369 . All
changes and supplementary course materials will be
available from this site. In addition, necessary
changes or important announcements will also be
distributed by e-mail. In order to receive
class-related messages you have to send an e-mail to
the instructor (huber@omega.uta.edu).
Office hours for the course will be held by the instructor in 114 GACB,
MW 8:30 - 9:15, and W 2:00 - 3:00. Times are subject to change and will be posted. If for some reason you can not make it to any of these office hours, please inform the instructor.
e-mail: huber@omega.uta.edu