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Nov 10, 2024
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CSC 216 - Decision Making Under Uncertainty in Computing
Semester Hours: 3
Periodically
Decision under uncertainty arises in many areas of computing where objectives must be achieved and actions must be taken using noisy data arising in uncertain, dynamic environments and containing only partial information. Such areas include artificial intelligence, sensor fusion and integration, sensor networks, computer vision, machine learning and mobile robotics. The course surveys formal frameworks for addressing such problems and finding admissible solutions. Topics include: probabilistic reasoning, Bayesian and minimax estimation, Bayesian networks, particle filters, fuzzy logic.
Prerequisite(s)/Course Notes:
CSC 204 . (Formerly Quantitative Approaches to Decision Making.)
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