Name | Room | Phone | ||
---|---|---|---|---|
Lecturer | Roland Bol | Roland.Bol@it.uu.se | 1356 | 018-471 7606 |
Lecturer | Mats Cedvall | Mats.Cedvall@it.uu.se |
2322 |
018-471
1029 018-471 2973 |
week |
day |
time |
room |
topic |
who |
reading |
assignments |
36 |
Tue 1 |
13 |
1111 |
What
is AI? History of AI. |
RB,MC, OG |
1, 16 |
|
Fri 4 |
10 |
1111 |
Search
introduction |
RB, MC |
3.0, 3.2 + more |
||
37 |
Tue 8 |
13 |
1111 |
Heuristic
search methods 8puzzle |
MC |
4.0-4.3, 4.5 |
1.
Short paper |
Fri
11 |
10 |
1211 |
Search
in playing games |
RB |
4.4 + more |
||
38 |
Mon 14 |
10 |
1211 |
lektion: search A* and alpha-beta |
MC/RB |
2. Game program |
|
Fri 18 |
8 |
1211 |
Knowledge
Representation, Planning |
RB |
7 (parts) 8.4 |
||
39 |
Tue 22 |
15 |
1311 |
Expert systems |
RB |
6.2 (part) 8.0-8.3 |
|
Fri 25 |
8 |
1211 |
Match midcourse evaluation introduction to learning |
RB |
10.1, 10.4 |
||
40 |
Mon 28 |
13 |
1211 |
Learning, inspired by
nature (Pdf 1.4M) |
OG |
11,12 (parts) |
|
Fri 2 |
8 |
1211 |
Learning
(induction, learning as
search) |
RB |
10.2.2, 10.3, 10.6.2 |
||
41 |
Mon 5 |
13 |
1211 |
Uncertainty Proposed solutions |
MC |
5.2-5.4 9.2, 9.3 |
3.
Implementing a small expert system in Match |
Mon 5 |
15 |
1211 |
Introduction
to Data Mining |
GG |
|||
Thu 8 |
15 |
1311 |
Understanding
natural language |
MC |
15.0-15.3 (not 15.2.2) |
||
42 |
Tue 13 |
15 |
1211 |
AI in computer games | OG | ||
Thu 15 |
15 |
1211 |
questions, solutions,
course evaluation |
RB, MC |
|||
43 |
Tue 20 |
8 |
Gimog |
exam, at Gimogatan
4, sal 1. |
|||
Jan |
Fr 15 |
8-11 |
Pol
5 |
re-exam, exam hall, Polacksbacken |
|||
Aug |
re-exam if required |