CSci 5511, Spring 2009: Syllabus

Class Information

Time/Room:	Monday and Wednesday 4:00pm-5:15pm in MechE 212
Instructor:	Dr. Maria Gini (gini at cs.umn.edu) office hours: Monday 10:00-11:00 and Wednesday 2:00-3:00 or by appointment in EE/CS 5-213, (612) 625-5582. Address: 4-192 EE/CSci Building, 200 Union St. SE, Mpls, MN 55455
TA:	Matt Kappel (kappel at cs.umn.edu), office hours: Thursday 2:30-3:30 and Friday 11:00-noon in 2-209 EE/CS

Textbook

Stuart Russell and Peter Norvig "Artificial Intelligence. A modern approach. 2nd Edition", Prentice-Hall, 2003. (Chapters 1-12).

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-2009/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.

Work Load and Grading Policy

Readings: Approximatively 30 pages of reading/week from the texbook and occasionally other papers.
Assignments:
- five written homeworks (40% of the grade). Homeworks will include problem solving and short Lisp programming problems.
  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.
- one project (10% of the grade). The project is on a topic of your own choice and can be done in groups of two.
Exams:
- three in class midterm exams (the first 10% of the grade, the second and the third 15% each),
Exams are open books and notes.
Participation: There will be an in-class exercise every week. Participation to the class activities will count for 10% of the grade.

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.

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.

Tentative Class Schedule (subject to changes)

	Ch	Topics	Assignments due	AIMA Slides
Week 1 - Jan 21	1, 2	Intro. Intelligent Agents		Chapter 2
Week 2 - Jan 26-28	3	Problem Solving and Search	Homework 1 Wed Jan 28	Chapter 3
Week 3 - Feb 2-4	3,4	Search		Chapter 4.1-2
Week 4 - Feb 9-11	4	Heuristic Search	Homework 2 Wed Feb 11	Chapter 4
Week 5 - Feb 16-18	5	Constraint Satisfaction		Chapter 5
Week 6 - Feb 23-25	5, 6	Constraint Satisfaction. Game Playing	First Midterm Exam Wed Feb 25	Chapter 6
Week 7 - Mar 2-4	6	Game Playing
Week 8 - Mar 9-11	7	Propositional Logic	Homework 3 Wed March 11 Project Proposal Wed March 11	Chapter 7
Week 9 - Mar 23-25	8	First-Order Logic		Chapter 8
Week 10 - Mar 30 - Apr 1	9	Inference in Logic	Homework 4 Wed April 1	Chapter 9
Week 11 - Apr 6-8	10	Knowledge Representation
Week 12 - Apr 13-15	10	Knowledge Representation	Second Midterm Exam Wed Apr 15
Week 13 - Apr 20-22	11	Planning		Chapter 11
Week 14 - Apr 27-29	11, 12	Planning	Homework 5 Wed Apr 29	Chapter 12
Week 15 - May 4-6	12	Planning	Third Midterm Exam Monday May 4	Project Friday May 8
		Monday May 11	No Final Exam