Foundations of Artificial Intelligence

CS 5100, Fall 2011

Announcements

Important announcements related to the course will be posted here. Please check this page regularly.

  • December 8 - Assignment 5 solutions have been posted on Blackboard.

  • December 8 - Extra credit assignment posted on Blackboard.

  • December 1 - The Final Exam will be held in room 135 Shillman Hall on December 15

  • November 17 - Assignment 5 posted on the website and Blackboard. Submission is due in class on December 1.

  • November 2 - Solutions to the Midterm have been posted on Blackboard under Course Material.

  • October 20 - Assignment 4 posted on the website and Blackboard. Submission is due through Blakboard by November 10.

  • October 19 - Midterm Exam will be held in room 135 Shillman Hall on October 27

  • October 7 - Solutions for Assignment 2 have been posted on Blackboard under Course Material

  • October 7 - Assignment 3 posted on the website and Blackboard. Submission of Part I is due in class on October 13 and Part II through Blakboard by October 20.

  • September 21 - Final Exam date finalized for December 15

  • September 15 - Assignment 2 posted on the website and Blackboard. Submission of Part I is due in class on September 29 and Part II through Blackboard by October 6 11:59 pm.

  • September 8 - Assignment 1 posted on the website and Blackboard. Submission is due through Blackboard by September 15 11:59 pm.

  • September 7 - Office hours for Prof. Sliva have changed.

  • September 2 - Classroom changed to 435 Ryder Hall.

  • July 14 - Class website is up and running!
    First day of class: September 8--6:00-9:00pm.

Instructor

Professor Amy Sliva
Office: 256 West Village H
Email: asliva@ccs.neu.edu
Office Hours: Th 3:30pm-4:30pm

Teaching Assistant

Abdorrahim Bahrami
Office: Computer Aided Reasoning Lab (LAB 316)
Email:mihar@ccs.neu.edu

Information

Course Description This course introduces the fundamental problems, theories, and algorithms of the artificial intelligence field. Topics covered include: automated deduction and problem-solving; heuristic search and planning; Bayesian inference and statistical learning methods; natural language processing. Required course work includes the creation of working programs that solve problems, reason logically, and/or improve their own performance using techniques presented in the course.
Lecture Location 435 Ryder Hall
Lecture Times Thursday 6:00-9:00pm
Textbooks Artificial Intelligence: A Modern Approach (3rd Edition) by Stuart Russell and Peter Norvig, Prentice Hall (2010) (ISBN 0-13-604259-7).
See the resources page for more useful online links and recommended texts.