CMSC 471, Fall 2007 - Course Schedule
Current as of 8/28/07

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Notes:

Class

Date

Topic

Reading

Homework

Comments
1 Wed 8/29 Course overview; What is AI? Ch. 1, Lisp Ch. 1, McCarthy paper Pretest and HW1(PW) out Slides
2 Wed 9/5 Agents/Lisp Ch. 2, Lisp Ch. 2-3, Graham article Pretest due Intelligent Agents Slides, LISP slides
3 Mon 9/10 Problem solving as search Ch. 3.1-3.3, Lisp Ch. 4-5, App. A   Slides
Lisp debugging handout
4 Wed 9/12 Uninformed search Ch. 3.4-3.7
Slides (see above)
Homework grading handout
5 Mon 9/17 Informed search Ch. 4.1-4.2, Lisp Ch. 7 HW1 due;
HW2(PW) out 		Slides
6 Wed 9/19 Optimization and local search Ch. 4.3, Genetic Algorithms   Slides (see above)
7 Mon 9/24 Constraint satisfaction Ch. 5.1-5.3   Slides
8 Wed 9/26 Game playing Ch. 6.1-6.3 Project description out Slides
9 Mon 10/1 Game playing II Ch. 6.4-6.7 HW2 due;
HW3(W) out 		 Slides (see above)
10 Wed 10/3 Knowledge-based agents Ch. 7.1-7.3 Project teams formed  Slides
11  Mon 10/8 Propositional logic Ch. 7.4-7.5, skim 7.7    Slides
12 Wed 10/10 First-order logic Ch. 8.1-8.3   Slides
13 Mon 10/15 Logical inference Ch. 9 HW3 due;
HW4(W) out 		Slides
14 Wed 10/17 Knowledge representation Ch. 10.1-10.2, 10.6 Project proposal due

Slides
In-class Resolution Refutation Problem
15 Mon 10/22 State-space planning Ch. 11.1-11.2   Slides
16 Wed 10/24 Partial-order planning Ch. 11.3   Slides (see above)
17 Mon 10/29 MIDTERM
HW4 due;
HW5(W) out
18 Wed 10/31 Scheduling and hierarchical planning Ch. 12.1-12.2   Slides
  Sat 11/3 The DARPA Urban Challenge in CA     This is AI history in the making!
19 Mon 11/5 Probabilistic reasoning Ch. 13.1-13.8   Slides
20 Wed 11/7 Bayesian networks Ch. 14.1-14.2, 14.4 (section on inference by enumeration only), 20.1-20.2 (through section on Naive Bayes Models) Project design due Slides
21 Mon 11/12 Machine learning I: decision trees Ch. 18.1-18.3 HW5 due; HW6(WE) out
 Slides
22 Wed 11/14 Machine learning II: decision trees, version spaces, Ch. 19.1   Slides (see above)
23 Mon 11/19 Machine learning III: k-nearest neighbor, support vector machines skim 20.4, 20.6-20.7 Tournament dry run #1 Slides
24 Wed 11/21 Machine learning IV: naive Bayes, neural networks, clustering, weka skim 20.5   Slides
25 Mon 11/26 Philosophy and history of AI Chronology of AI; Ch. 26, Turing article; Searle article   Slides
26 Wed 11/28 Robotics Ch. 25.1-25.2, skim 25.3-25.4, 25.7-25.8   Slides
27 Mon 12/3 AI in Games / Natural Language Processing Ch. 22.1-22.2   GameAI slides, NLP slides
28 Wed 12/5 Review
HW6 due Tournament dry run #2 (by Friday)
29 Mon 12/10 Tournament
Tournament
-- Wed 12/19 FINAL EXAM, 1:00pm - 3:00pm   Project and final report due  


* Special topics courses are subject to change.