Lectures: MW 1:30-3:00pm
The course will cover algorithms and techniques that have already been used widely in the field as well as open research problems and approaches at the edge of the state of the art in these fields. The target audience for this course are primarily graduate students who are interested in Artificial Intelligence or its applications to problems in other areas of computer science (e.g., computer networks, intelligent databases, information retrieval, program synthesis, automated discovery, automated design, robotics, operating systems, parallel and distributed computing). Interested undergraduates who have completed ComS 472 with a grade of A- or better are welcome to register for the course (as special topics ComS 590VH).
Prerequisites: An introductory (senior undergrad or first year grad) course in AI is recommended. However, anyone with a sufficiently broad background in Computer Science (e.g., a few 500-level CS courses at ISU or comparable courses taken elsewhere) should find the material accessible.
Grading in this course will be based on problem sets (25%), preparation of lecture notes and participation in classroom discussions (25%) and one or more term projects or papers. There will be no examinations.
Please mail suggestions for changes and additions to: honavar@cs.iastate.edu