CSC 384H: Syllabus

Syllabus

This page describes the topics and assigned reading for the course. If no source is specified, assume that the reference is from Artificial Intelligence: A Modern Approach (2nd edition), by Russell & Norvig.

Week	Topics	Reading and Activities
1	Introduction to artificial intelligence (definitions, areas, etc.) and outline of course goals. Agents & multi-agent systems.	Chap 2 (all sections)
2	Searching techniques (breadth-first, depth-first, etc.) Uninformed and heuristic search.	Chap 3 (all sections) Chap 4, Sect 4.1 - 4.3
3	Game-playing algorithms Application of heuristics to game domains	Chap 6 (all sections) Sect 17.6
4	Reasoning & Logic (predicate logic, first-order logic) Performing logical inferences	Chap 7,8,9 (all sections)
5	Planning	Chap 11 (all sections except 11.4) Chap 12 (all sections)
6	Expert Systems Decision Trees	Chap 18, Sect 18.2 - 18.4
7	Natural Language Processing speech recognition syntactic analysis semantic processing	Chap 22, (all sections)
8	Probability for AI	Chap 13, (all sections) Chap 14, Sect 14.1, 14.6, 14.7 Chap 15, Sect. 15.1, 15.2
9	Statistical Natural Language Processing	Chap 23, (all sections)
10	Hidden Markov Models	Chap 15.1, 15.2, 15.3, 15.6
11	Learning (statistical)	Chap 20.1, 20.2, 20.3, 20.4
12	Neural Networks	Chap 20.5, 20.6
13	Vision	(no lecture slides) Chap. 24