6.825: Techniques in Artificial Intelligence--Fall '06

Announcements
References
Syllabus
Description
Prerequisites
Grading
Collaboration
Previous Editions


Course Staff Lectures

Professor: Tomas Lozano-Perez
tlp@csail.mit.edu
Office: 32-G492
Office Hours: Thursdays 4:30pm-5:30pm, or by appointment
Staff Mailing List: 6825-staff@csail.mit.edu

TA: Han-Pang Chiu
chiu@csail.mit.edu
Office: 32-G436
Office Hours: Tuesdays 4:30pm-6:00pm, or by appointment

Tuesdays and Thursdays,
2:30 - 4:00 pm
Location: 32-124

Announcements

References

Syllabus

Includes pointers to required reading not in the textbook and suggested exercises.

Description

6.825 is a graduate-level introduction to artificial intelligence. Topics include: representation and inference in first-order logic; modern deterministic and decision-theoretic planning techniques; basic supervised learning methods; and Bayesian network inference and learning.

Prerequisites

  • 6.041 (Probabilistic Systems Analysis)
  • 6.042 (Mathematics for Computer Science)
  • 6.046 (Introduction to Algorithms) (desirable, but not required)

Students should be familiar with uninformed search algorithms (depth-first and breadth-first methods), discrete probability (random variables, expectation, simple counting), propositional logic (boolean algebra), basic algorithms and data structures, basic computational complexity, and basic calculus. Students should also be aware that course assignments will require the use of the Java programming language.

Grading

The work for this course will consist of four take-home project assignments and two exams: a quiz and a final. The projects will count for 50% of the grade (5% for Proj 0, 15% each of Projs 1, 2, 3), and the exams, 50% (20% for the quiz and 30% for the final).

Late Policy for Projects: 10% off for each calendar day late. No credit if more than 5 days late.

Collaboration

We want to strongly encourage collaboration as a way for students to come to understand the material better. Projects 0 and 1 are individual assignments, but you may do Project 2 and Project 3 in groups of two, turning in a single write-up. You do not have to partner with the same person for both of the projects and you can choose to do either or both of them on your own.

If you are looking for a partner for an assignment, email the class list asking if anyone is available. You are also quite welcome to discuss the assignments as much as you'd like between groups. The ultimate requirement is this: Don't put your name on anything you don't understand. There will, of course, be no collaboration allowed on the exams.