CS 5100 Artificial Intelligence
Spring 2010
Course Description and Syllabus
Instructor: Prof. Carole Hafner hafner@ccs.neu.edu, Office: 446 West
Village H, Tel. 617-373-5116
Course web site: http://www.ccs.neu.edu/course/csu120/
Class Meets: Thursdays 6-9 p.m. 012 Hayden Hall
Prof. Hafner Office Hours: Wed 4-6
This course introduces the fundamental concepts, models and techniques
of the artificial intelligence field, along with examples of
applications. Topics covered
include: automated deduction and problem-solving; heuristic search and
planning; bayesian inference and statistical learning methods; natural
language processing.
Required coursework includes the creation of working programs that
solve problems, reason logically, and/or improve their own performance
using techniques presented in the course.
Required Textbook: Artificial
Intelligence: A Modern Approach, 3rd
Edition by Stuart Russell and
Peter Norvig. (Prentice Hall 2010).
BE
SURE TO GET THE THIRD EDITION -- it is significantly different (and
better) than the 2nd edition!!!!!!!!!!!!!!!
Strongly Recommended: Learning Python
by Mark Lutz (Prentice Hall, 2008).
There will be 5 or 6 homework assignments, containing written and/or
programming problems. We will be using Python, a relatively new
language that is rapidly replacing Lisp and Perl as the preferred
language for AI programming. There will be two exams: an in-class
midterm exam and on-line final exam.
In order to become acquainted with applications as well as the
fundamentals of AI, students will work in teams to study an application
paper, and present a 20 minute talk to the class describing the
application and summarizing the paper. The papers will be
selected from the annual IAAI conference (Innovative Applications
of Artificial Intelligence) or from AI Magazine (selections from AI
magazine must be pre-approved by the professor to be sure they qualify
as "application papers"). The presentations will take place
during the last three weeks of the semester.
Assignments will be available in the Assignments
Directory
Sample Programs will be available in the
Sample Programs Directory
Class notes will be available on the Class Notes
Directory
Additional links and information about resources will be available on
the course Resource
Page.
The schedule for appplication
paper presentations will be posted here.
WEEK
|
Topics
|
Readings
|
|
|
1
1/14
2
1/21
3
1/28
4
2/4
|
Introduction;
Problem Solving by Deductive Inference; Learning Python
|
RN 2.1, 2.2, 2.4
|
|
|
RN 7.1-7.7
|
|
|
RN Ch. 8 (review??)
RN 9.1-9.4
|
|
|
RN 9.4 (cont.)
RN 10.1-10.3
|
|
|
5
2/11
6
2/18
7
2/25
|
Search
and Planning
|
RN 3.1-3.5; 4.1-4.2
|
|
|
RN 4.3, 5.1-5.2
|
|
|
RN 11.1-11.3
|
|
|
8
3/4
|
Spring Break
|
RN Ch. 13 (review??)
|
|
|
9
3/11
|
Midterm Exam
Probability and Evidence (intro)
|
|
|
|
10
3/18
11
3/25
12
4/1
|
Probabilistic
Inference/Machine Learning
|
RN Ch. 14.1-14.4; 14.7
|
|
|
RN 15.1-15.3
|
|
|
RN 18.1-18.3; 20.1-20.2;
RN 20.5
|
|
|
13
4/8
14
4/15
15
4/22 |
Natural
Language Processing
|
RN 22.1-22.4
|
|
|
RN 22.5-22.7
|
|
|
RN Ch. 23
|
|
|
|
On-line final exam: Thursday
April 29, 6:00 p.m. - 10:30 p.m.
|
|
|
|
Course Administration and Rules
Approximately 40% of the course grade will be determined by
individual assignments, 50% by the midterm and final exams, 10% by the
presentation.
Class participation will also be taken into account in determining the
course grade. Late
assignments may be discounted, and very late assignments may be
discarded.
Academic Honesty: The individual assignments must be each student's
own
work. Any group projects assigned must be the work of the
students in
the group. Plagiarism or copying will result in official
University
disciplinary review.
Security is an important aspect of computer science. Students are
expected to protect their work
from plagiarists.
There are no make-up exams in this course.
Normally if a student misses an exam the student will receive a
grade
of 0 on that exam. Under unusual circumstances (such as documented
serious illness), the student's grade on a missed exam will be replaced
by the grade on the final exam.
The final exam will be posted on the Web at 6pm on the official final
exam date, which is Thursday, April 29. It will be available in
both
html and MS Word (.doc) format. Your completed exam must be sent
by email to Prof. Hafner (hafner@ccs.neu.edu) by 10:30 p.m. the same
day, April 29. Students will be required to state that the exam
is their own work, and that they did not receive assistance from other
people.
Last modified: January 12, 2010