syllabus
ARTIFICIAL INTELLIGENCE - CDS34
4 CR MTh 1:30 - 2:50 Sci 217 Intermediate
Faculty: Jim Mahoney
An examination of the methods used in problems encountered in trying to teach computers to "think."
Topics covered will be among the following: representation of knowledge, learning, game theory, perception, neural networks, cellular automata, cognitive modeling, and natural language processing.
Most people who work in AI program in Lisp, and so we will likely use it as well (learn it along the way), but that won't be the main focus of the course. This is an intermediate course in computer science and as such assumes previous programming experience.
Prerequisite: Substantive programming experience
approximate schedule
week Monday chapter topic college
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1 Sep 3 1 background intro classes Wed/Thur 5/6
2 10 2 searching
3 17 3 agents
4 24 4,5 more search
5 Oct 1 6 games
6 8 7 logic mid-term evals due Fri 12
7 15 8 inference
8 22 9 FOL Hendrick's Days Mon/Tues
9 29 10 knowledge
10 Nov 5 13 probability/Bayes
11 12 18 learning
12 19 Thanksgiving break Wed-Fri
13 26 20 neural nets
14 Dec 3 24 perception
15 10 26,27 philosophy last day of classes Wed 12
17 final grades due Wed 19
