Schedule of Topics for CIS630 - Artificial Intelligence 1

Lectures will cover material from the book according to this schedule. You are expected to have read the indicated textbook chapter before coming to class.

Lectures will be hopefully be posted sometime during the week, but I reserve the right to change the lecture notes anytime up to the lecture, so the only way to get the definitive version is to get the notes during the next week. Lecture notes are only available via the ohio-state.edu domain.

March/April

Week # Sunday Monday Tuesday Wednesday Thursday Friday Saturday
I
Intro
Slides: pdf
28
29
Preliminaries
What is intelligence?
Read: Chapter 1
30
31
What is Intelligence? (ctd)
Agents
Read: Chapter 2
HW1 out: agents
1
2
Agents (ctd)
3
II
Search
Slides: pdf (full)
4
5
Uninformed search
Read: Chapter 3
6
7
Uninformed search (ctd)
HW2 out: search
8
9
Informed Search
Read: Chapter 4
10
III
Search
Slides: pdf (full)
11
12
Informed Search (ctd)
Hill Climbing
HW1 due
13
14
Hill Climbing (ctd)
Genetic Algorithms
15
16
Adversarial Search (Games)
Read: Chapter 6
17
IV
Logic/Exam
Slides: pdf
18
19
Logical Agents,
Inference in Prop Logic
Read: Chapter 7
HW2 due
20 21
First-order logic
Read: Chapter 8
22
23
EXAM I
Ch 1, 2, 3, 4, 6
24
V
Logic
Slides: pdf
25
26
First-order logic (ctd)
HW3 out: logic and inference
27
28
Inference in Pred Logic
Read: Chapter 9
29
30
Finish up logic
1

May/June

Week # Sunday Monday Tuesday Wednesday Thursday Friday Saturday
VI
Video/Planning
Slides: pdf
2
3
AI Video
4
5
AI Video
6
7
Planning
Read: Chapter 11
HW4 out: Planning
8
VII
Planning/Exam
Slides: pdf
9
10
Planning (ctd)
HW3 due
11
12
Multi-agent Planning
Read: Section 12.7
13
14
Exam II
Chapter 7, 8, 9, 11, Video
15
VIII
Uncertainty/Decisions
Slides: pdf
16
17
Uncertainty
Read: Chapter 13
HW4 due
18
19
Uncertainty (ctd)
HW5 out: uncertainty, decision theory
20 21
Decision theory
Read: Chapter 16
22
IX
Decisions/Learning
Slides: pdf
23
24
Decision theory (ctd)
25 26
What is learning? Read: Ch. 18.1-18.2
27 28
Complex decisions,
Reinforcement Learning
Read: Chapter 17.1-17.2, 21.1-21.3
HW5 due
HW6 out: learning
29
X
Wrapup
Slides: pdf
30
31
HOLIDAY
No class
1 2
AI: Present and Future
Read: Chapter 27
3 4
Review
HW6 due
5
(XI)
6
7
Comprehensive Final Exam
7:30 - 9:18 am
8
9
10
11
12

Eric Fosler-Lussier
Last modified: Thu Jun 3 16:16:03 EDT 2004