CSCI 509-2 Foundations of Bayesian Networks

Prerequisites: CSCI 220 (Data Structures and Algorithms) and CSCI 330 (Programming Language Structures); or graduate standing in Computer Science, Statistics, Mathematics, Computer Engineering, Electrical Engineering, or Management Science.

Instructor: Marco Valtorta
Office: Sumwalt 206A, 777-4879
E-mail: mgv@cs.sc.edu
Office Hours: MF 9:30am-11:15am, W 2pm-3:15pm (Note change!), or by previous appointment

The goals of this course are:

• To introduce the area of uncertainty in artificial intelligence.
• To study probabilistic and causal modeling with Bayesian networks.
• To provide skills in computer-based decision analysis, with salient examples.
• To explain the Hugin Bayesian network and influence diagram tool.

Syllabus and Required Texts

Lecture Log