Foundations of Artificial Intelligence

CS4700 - Fall 2008
Cornell University
Department of Computer Science

Time and Place

CS4700

First lecture: Friday, August 29, 2008
Last lecture: Friday, December 5, 2008

Monday, 11:15am - 12:05pm in PH 101
Wednesday, 11:15am - 12:05pm in PH 101
Friday, 11:15am - 12:05pm in PH 101

Midterm (in-class): Wednesday, October 8.
Final Exam: From 02:00 PM to 04:30 PM on Fri Dec 12 2008. PHL101

CS4701 (Optional)

Organizational meeting

Tuesday, September 2^nd at 3:35pm, in Hollister Hall room 110.

Instructor Prof. Carla Gomes, gomes @cs.cornell.edu, 5133 Upson Hall.

Head Teaching Assistants

Yunsong Guo guoys @cs.cornell.edu

Anton Morozov amoroz @cs.cornell.edu

Teaching Assistants

Clayton Chang cc843@cornell.edu

Sean Sullivan sps27@cornell.edu

Daniel Perelman dap56@cornell.edu

Joel Ong jyo2@cornell.edu

Adam Yeh aby4@cornell.edu

Administrative Assistant

Kelly Duby <kduby@cs.cornell.edu>, 4105 Upson Hall.

Office Hours

Time	Name	Location
Mon 4:00-5:00pm	Anton Morozov	328UP, bay b
Tue 5:30-6:30pm	Yunsong Guo	RH457
Wed 1:20-2:20pm	Daniel Perelman	328UP, bay b
Thur 3:00-4:00pm	Adam Yeh	328UP, bay b
Thur 5 :30-6:30pm	Clayton Chang, Sean Sullivan	328UP, bay b
Fri 1:15-2:15pm	Prof. Gomes	UP5133

Mailing List

cs4700ta-l "at" lists.cs.cornell.edu. (Note: Remove the extra spaces). We'd like you to contact us by using this mailing list. The list is set to mail all the TA's and Prof. Gomes -- you will get the best response time by using this facility, and all the TA's will know the question you asked and the answers you receive.

Reference Material

The main textbook for the class is:
Artificial Intelligence: A Modern Approach, Russell and Norvig, Prentice-Hall, Inc., second edition. I’ll refer to the book as “R&N”.

Prerequisites

This course has no prerequisites other than familiarity with basic data structures and programming (e.g., CS211) and the basic mathematical skills obtained in CS280. An understanding of inference in prepositional logic and basic blind search techniques (i.e., breadth-first and depth-first search) is also assumed, but background readings in these topics can be provided for those with a deficiency in this area.

Syllabus

This course introduces the theoretical and computational techniques that serve as a foundation for the study of artificial intelligence (AI). Topics to be covered include the following:

Introduction of AI and background: What is AI? Related fields.
Problem solving by search: principles of search, uninformed (“blind”) search, informed (“heuristic”) search, and local search.
Constraint satisfaction problems: definition, search and inference, and study of structure.
Adversarial search: games, optimal strategies, imperfect, real-time decisions.
Logical agents: propositional and first order logic, knowledge bases and inference.
Uncertainty and probabilistic reasoning: probability concepts, Bayesian networks, probabilistic reasoning over time, and decision making.
Learning: inductive learning, concept formation, decision tree learning, statistical approaches, neural networks

Note: some of the topics listed above may be covered only briefly, depending on time. Detailed reading information will be provided in the lectures notes and homework assignments.

Grading CS4700 --- This is a 3-credit course. Grades will be determined based on a midterm, a final exam, homework assignments, and class participation.

15%: Midterm
35%: Final Exam
45%: Homework (~6 assignments)
5%: Participation

The midterm is an in-class examination (Wednesday, Oct 8) and the final will be given on the day and time slot scheduled by the university. All assignments are due at the beginning of class on the due date. Assignments turned in late will drop 20 points for each period of 24 hours for which the assignment is late. In addition, no assignments will be accepted after the solutions have been made available.

Re-grading: Although you are encouraged to talk with any TA about the questions, only the head TAs may award back points (or detract points if they find new things wrong) if you want a re-grade.

CS4701 Project (Optional)

You may take CS4701 "Practicum in Artificial Intelligence" as a supplement to CS4700. CS4700 is a co-requisite for CS473. There will be an organizational meeting in Hollister Hall room 110 on Tuesday, September 2^nd at 3:35pm.

The main assignment for CS4701 is a course project. Students will work in groups (probably pairs). A project proposal is required. A separate project handout with project suggestions, details, and due dates regarding the project proposal, and final project write-up will be made available from the course home page.

Grading CS4701

20%: Project proposal
80%: Final code, write-up, and presentation

Academic Integrity

This course follows the Cornell University Code of Academic Integrity. Each student in this course is expected to abide by the Cornell University Code of Academic Integrity. Any work submitted by a student in this course for academic credit is expected to be the student's own work. Collaboration is allowed as prescribed above, but you cannot copy all or part of another student's homework or program --- regardless of whether that copy is on paper or on-line. Violations of the rules (e.g. cheating, copying, non-approved collaborations) will not be tolerated.

CS4700 Lecture Notes

CS4701 Webpage

Homework Assignments

Homework assignments are available via CMS. Assignments are due in hardcopy. Graded homework assignments and the midterm can be picked-up in Upson 360.