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2009-2010 University Catalog
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CSI 775 - Computational Models of Probabilistic ReasoningCredits: 3
Cross-Listed with OR 719/STAT 719
Introduces theory and methods for building computationally efficient software agents that reason, act, and learn environments characterized by noisy and uncertain information. Covers methods based on graphical probability and decision models. Students study approaches to representing knowledge about uncertain phenomena, and planning and acting under uncertainty. Topics include knowledge engineering, exact and approximate inference in graphical models, learning in graphical models, temporal reasoning, planning, and decision-making. Provides practical model building experience. Students apply what they learn to semester-long project of their own choosing.
Prerequisites
STAT 652 or 664, or permission of instructor.
Hours of Lecture or Seminar per week
3
Hours of Lab or Studio per week
0
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