CSci 5511, Fall 2008: Syllabus

Class Information

Time/Room:	Tuesday and Thursday 4:00pm-5:15pm in MechE 108
Instructor:	Dr. Maria Gini (gini at cs.umn.edu) office hours: Monday 2:00-3:00 and Thursday 11:00-12:00 or by appointment in EE/CS 5-213, (612) 625-5582. Address: 4-192 EE/CSci Building, 200 Union St. SE, Mpls, MN 55455
TAs:	Baylor Wetzel (wetz0025@umn.edu), office hours: Wed 2:30-3:30 in 2-209 EE/CS Matt Kappel (kappel at cs.umn.edu), office hours: Tuesday 1:30-2:30 in 2-209 EE/CS

Textbook

Stuart Russell and Peter Norvig "Artificial Intelligence. A modern approach. 2nd Edition", Prentice-Hall, 2003. (Chapters 1-11).

You should go to http://aima.cs.berkeley.edu/lisp/doc/install.html to download the Lisp software from the texbook. We will use it for some homeworks.

You'll need reference material on Lisp. Here are some choices:

Lamkins, Successful Lisp: How to Understand and Use Common Lisp, bookfix.com, 2004.
Graham, ANSI Common Lisp, Prentice Hall, 1996
The Lisp Code, the text of the first two chapters, and many articles on Lisp are available from http://www.paulgraham.com/

All class material will be posted at http://www.itlabs.umn.edu/classes/Spring-2008/csci5511/.

Prerequisites

Students are expected to have the following background:

Knowledge of basic computer science principles.
Knowledge of data structures (graphs and trees).
Knowledge of formal logic (propositional and predicate logic).

Course Description

This course provides a technical introduction of fundamental concepts of artificial intelligence (AI). Topics include: history of AI, agents, search (search space, uninformed and informed search, constraint satisfaction, game playing), knowledge representation (logical encodings of domain knowledge, logical reasoning systems), planning, and the language Lisp. The course is suitable for students who want to gain a solid technical background and as a preparation for more advanced work in AI.

Course Requirements

five written homeworks (40% of the grade). Homeworks will include problem solving and short Lisp programming problems;
one project (10% of the grade). The project is on a topic of your own choice and can be done in groups of two.
participation to class discussion and in class activities (10% of the grade).
two in class midterm exams (each 10% of the grade),
one final exam (20% of the grade).

Academic Integrity

All work submitted for this class must represent your own individual effort unless group work is explicitly allowed. You are free to discuss course material and approaches to problems with classmates, the TAs, and the professor (and you are encouraged to do so), but you should never misrepresent someone else's work as your own. It is also your responsibility to protect your work from unauthorized access. Collaboration on homework or exams is cheating and grounds for failing the course. Any student caught cheating will receive an F as a class grade and the University policies for cheating will be followed. In addition, any graduate student caught cheating will be subject to the Department policy on cheating.

Policy on Exams and Grading

Grades will be assigned on the following scale: 93% and up will earn you an A 90% to 93% an A-, 87% to 90% a B+, 83% to 87% a B, 80% to 83% a B-, 75% to 80% a C+, 65% to 75% a C, 60% to 65% a C-, 55% to 60% a D+, 50% to 55% a D, below 50% an F.
Exams are open books and notes. Late Homeworks will lose 10% of the maximum total points for every weekday late. Late homeworks will be accepted up to a week after they are due. Keys will be distributed in class a week after the homework is due.

Tentative Class Schedule (subject to changes)

	Ch	Topics	Assignments due	AIMA Slides
Week 1 - Sep 2-4	1, 2	Intro. Intelligent Agents		Chapter 2
Week 2 - Sep 9-11	3	Problem Solving and Search	Homework 1 Tuesday Sep 9	Chapter 3
Week 3 - Sep 16-18	3,4	Search		Chapter 4.1-2
Week 4 - Sep 23-25	4	Heuristic Search	Homework 2 Tuesday Sep 23	Chapter 4
Week 5 - Sep 30-Oct 2	5	Constraint Satisfaction		Chapter 5
Week 6 - Oct 7-9	5, 6	Constraint Satisfaction. Game Playing	First Midterm Exam Tuesday Oct 7	Chapter 6
Week 7 - Oct 14-16	6	Game Playing
Week 8 - Oct 21-23	7	Propositional Logic	Homework 3 Tuesday Oct 21 Project Proposal Thursday Oct 23	Chapter 7
Week 9 - Oct 28-30	8	First-Order Logic		Chapter 8
Week 10 - Nov 4-6	9	Inference in Logic	Homework 4 Tuesday Nov 4	Chapter 9
Week 11 - Nov 11-13	10	Knowledge Representation
Week 12 - Nov 18-20	10	Knowledge Representation	Second Midterm Exam Tuesday Nov 18
Week 13 - Nov 25	11	Planning		Chapter 11
Week 14 - Dec 2-4	11, 12	Planning	Homework 5 Tuesday Dec 2	Chapter 12
Week 15 - Dec 9	12	Planning	Project Tuesday Dec 9
		Tuesday Dec 16	Final Exam, 4:00-6:00