Syllabus • Schedule • Academic Integrity • Piazza Page

Please note:

 • All readings refer to chapter sections in the textbook.
 • Pre-readings should be done before class.
 • All the reading material is covered on exams, so please make sure to bring questions about it to class.
 • Due dates are the night before the listed class. For example, homework 1 is due on 9/19 at 11:59, the night before the 9/20 class.

The schedule:

This is a tentative schedule.  Topics, reading assignments, homeworks, and exam dates are subject to change.

class date topic / slides pre-readings readings homework handouts / notes
1 9/1 Introduction and overview Class web page
Integrity policy
 Ch. 1 Intro survey out
Policies signature out
Intro & URLs
2 9/6 Agents 2.1, 2.2 intro, 2.2.1;
skim 2.3.1-2.3.2		 Ch. 2 Survey due
Policies signature due
By 11:59 9/5—see above
HW1 out
3 9/8 Problem solving as search 3.1 intro, 3.1.1, skim 3.3 Ch. 3.1–3.3
4 9/13 Uninformed search 3.4 intro, 3.4.1–3.4.3 Ch. 3.4
5 9/15 Informed search 3.5 intro, 3.5.1, skim 3.5.2 Ch. 3.5–3.7
6 9/20 Local search, genetic algorithms 4.1 intro, 4.1.1 Ch. 4.1–4.2 HW1 due
HW2 out
7 9/22 Constraint Satisfaction 6 intro, 6.1 intro, 6.1.1 Ch. 6.1–6.4 (skip 6.3.3)
supplement:
Vipin Kumar Survey
8 9/27 Game playing 5 intro, 5.1 Ch. 5.1–5.3, 5.4.1, 5.5
9 9/29 Probabilistic reasoning 13.2.1-13.2.2 Ch. 13 Be sure that you understand the concepts: random variables, prior probabilities, conditional probabilities, the product rule, and the joint probability distribution. It is essential that you understand the math in Ch. 13!
10 10/4 Bayesian networks Really understand Ch. 13 Ch. 14.1–14.4.2; skim 14.3 HW2 due
HW3 out
11 10/6 Decision making under uncertainty 15.1 Ch. 15.1–15.2.1, 16.1–16.3
12 10/11 Multi-agent systems Ch. 17.5–17.6 Project teams formed
13 10/13 Project review, games
Midterm review		 Project description out
Teams information (only one person has to fill this out)
new_eleusis.py UPDATED.
new_eleusis_test.py
A short README
14 10/18 ML 1: Concepts, decision trees 18.2 Ch. 18.1–18.3
15 10/20 ML 2: Other techniques 20.1 Ch. 20.1–20.2 HW3 due
Note extended date
HW4 out
16 10/25
Midterm: through multi-agent systems
17 10/27
Sick Day
18 11/1 Knowledge-based agents, propositional logic 7.4.1-7.4.2 Ch. 7 Project design due
at 11:59pm, 10/31
19 11/3 First-order logic 8.2, 9.5 Ch. 8.1–8.3
20 11/8 Knowledge-based agents, Logical inference Ch 9
(tbd)		 HW4 due
HW5 out
21 11/10 Knowledge Representation, Planning Ch. 12.1–12.2, 12.5–12.6
22 11/15 State space and partial-order planning Ch. 10.1–10.2, 10.4.2–10.4.4
23 11/17 Probabilistic planning Ch. 17.1–17.2.2, 17.4.1 Ch. 17.1–17.3
24 11/22 Guest lecture: Dr. Hamed Pirsiavash - Vision and Learning HW5 due
HW6 out cancelled
11/24 Thanksgiving Day
25 11/29 Reinforcement learning Ch. 21.1–21.3 Project phase 1 code due
Note extended date
26 12/1 Clustering and EM
27 12/6 Applications: Robotics
28 12/8 Applications: Natural Language Project phase 2 code due
29 12/13 Review Project phase 2 code due 11:59pm, 12/12
Project final survey due 11:59pm, 12/22 ←←
Final Review 12/16 Final review slides
Final 12/20 Final exam, 10:30am-12:30pm

This class is closely patterned after Dr. Marie desJardin's excellent AI class, with thanks.