CSCE976, Spring 2002: Advanced Artificial Intelligence
Prereq: CSCE876,
or equivalent. CSCE821 strongly recommended
Course description (from Graduate Program Guide to Policies and Requirements):
This
is a course for students with some sophistication and considerable interest
in exploring methods of designing and using algorithms useful for finding
adequate answers to combinatorial large problems that require largely symbolic
rather than numeric computing. It will be assumed that students are highly
proficient in one or more high level computer languages and either are
or will be able to function in functional and descriptive languages such
as LISP and PROLOG. The goal of the course will be to study, analyze
and critique basic and current research papers and to engage in artificial
intelligence projects and experiments either alone or in small groups.
Topics of study will include artificial intelligence environments, tools
and expert systems building. Class participation will be encouraged for
the review of the more recent AI literature.
The content of this course is modified every year. This year, we will
focus on the following topics: planning, temporal reasoning, distributed
constraint satisfaction, scheduling, spatial reasoning, distributed
problem-solving (multi-agent systems), and/or intelligent tutoring.
Time:
Monday, Wednesday, from 2:30 to 3:45 p.m.
Place:
CBA 141
Instructor: Prof. Berthe Y. Choueiry
Room 104, Ferguson Hall
choueiry@cse.unl.edu
Tel: (402)472-5444
Office hours: Monday, Wednesday 3:45--4:45 p.m.
or by appointment
Important:
Regularly check out the page of for reference to required and recommended
reading material, homework texts, and announcements.
Protocol of the course:
Mainly discussions of technical papers, otherwise lectures by the instructor
and presentations by students.
Absence: maximum 3 sessions, advanced notice required.
Collaboration and discussion within and outside the classroom strongly
encouraged unless specified (e.g., for assignments, quizzes, or `riddles').
Grading policy:
-
Students will be able to `compose' their grade, for up to 70% of the
total grade, from the following menu:
-
Presentation of a research paper by a student: 20%. (Grading:
clarity 20 points, organization 20 points, summary of contributions 30
points, critical analysis 30 points, interaction with and responsiveness
to audience 10 makeup points.)
-
Scribe of a discussion topic or a paper presentation or a critical
summary of a research paper: 5%. A student takes notes of an
entire discussion of a topic. One or more other students criticize the
notes of the scribe and rate the minutes (Excellent, Good, Satisfactory,
or Poor).
-
Project (programming): 30% (mainly for students who have taken 476/876
and 421/821)
-
Term paper: 30%. (mainly for students who have taken 476/876 and 421/821)
-
The remaining 30% are allocated as follows:
-
Surprise quizzes (mainly) and assignments (minimal): 20%.
-
Class interaction and participation in discussions are (subjectively) evaluated
for 10% of the total grade.
How can I improve my grade?
-
A bonus will be offered for a 100% attendance, starting second week of
semester.
-
Do the weekly and final glossaries: 5% (total). Students who return
every Monday, before class a glossary of terms listed in handouts will
receive
a bonus. Rules for glossary:
-
Students will be have to build an incremental and alphabetically sorted
glossary of important terms.
-
Terms to be included are the ones listed in the handouts distributed in
class or sent my email.
-
A glossary entry can be filled with: (1) its definition in AIMA, (2) its
definition from another AI textbook or dictionary, or (3) the student own
interpretation.
-
All terms encountered during a week are due as a weekly glossary the following
Monday.
-
At the end of the course, the full alphabetically sorted glossary is due.
(Hint: choose a text editor that can sort entries alphabetically.)
Grade conversion:
|
>97%
|
A+
|
|
94-96
|
A
|
|
90--93
|
A-
|
|
87--89
|
B+
|
|
84--96
|
B
|
|
80--83
|
B-
|
|
75--79
|
C+
|
|
67--74
|
C
|
|
60--66
|
C-
|
|
57--59
|
D+
|
|
54--56
|
D
|
|
51--53
|
D-
|
|
<=50
|
F
|
Textbooks:
No specific textbook is required for this course. We will mainly
use technical papers and sometimes chapters out of AIMA (the textbook of
476/876).
As the need arises, copies will be made available by, or can be retrieved
from, the instructor.
Main AI textbooks are available from the reserve desk or at Level 1A of
the Love Library (see below).
Books on reserve at the Love Library:
AI:
LISP:
Specific topics:
-
Foundations of Constraint Satisfaction by Edward Tsang.
-
A mathematical introduction to logic by Enderton, Herbert B, CALL NO. QA9
.E54 1972.
More books:
Useful links:
Some research groups involved in planning:
Berthe Y. Choueiry