CSC384 Course Information

Recent Announcements:

  1. Final exam is scheduled for Wednesday 16th Dec in the morning from 9:00 to 12:00.
  2. Office hours on Monday 14th Dec, from 1:00 to 3:00 pm (13:00 to 15:00), and on Tuesday 15th from 12:00 noon to 2pm (12:00 to 14:00).

 

 

Fall 2015 Offering: Section L0101:

    
Lectures: Tuesday and Thursday @ 1:00 to 2:00pm, Room MP102
Tutorials: Thursday @ 1:00pm in Room MP 103

 

Instructor: Fahiem Bacchus. Room 398E D.L. Pratt Building (PT398). fbacchus@cs.toronto.edu

    
You must put CSC384 in the subject line of all email related to the course. Unmarked email might be automatically deleted.

 

Office Hours Before Exam (for Fall 2015 CSC384):

  1. Monday 14th Dec, from 1:00 to 3:00 pm (13:00 to 15:00)
  2. Tuesday 15th from 12:00 noon to 2pm (12:00 to 14:00)

 

Course Web Page (Fall 2015): http://www.cs.toronto.edu/~fbacchus/csc384/

 

Course Information Sheet: PDF copy (Read!)

 

E-Mail: Please read the course information sheet prior to sending e-mail. (I won’t explain course material or assignments by e-mail).

 

Course Bulletin Board accessible via: https://csc.cdf.toronto.edu/ (please note that the board will not be moderated).

 

Outline: The course is an introduction to Artificial Intelligence. Artificial Intelligence as studied in Computer Science (i.e., as studied in this course) focuses on computational intelligence, i.e., trying to understand the computational principles behind intelligent behavior. The central premise thus being that intelligence is a computational process. One outcome of this endeavor has been the development of a number of theories, mathematical formalisms, and algorithms, that capture (or approximate) some of the core elements of computational intelligence. In this course we will study a number of these theories and algorithms. Besides achieving an understanding of some of the fundamental ideas in AI, the course also aims to provide you with ideas and tools that can be applied usefully in the production of "semi-intelligent" artifacts, i.e., artifacts that display some limited but useful amounts of intelligence.

The topics we will introduce in the course include:

  1. Search.
  2. Logical representations and reasoning.
  3. Classical automated planning.
  4. Representing, reasoning and decision making under uncertainty.

 

Recommended Texts:

  1. Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig. 3nd Edition. AIMA has a useful home page: http://aima.cs.berkeley.edu/ This is the most popular book on AI and it gives an introduction to many other topics in AI than will be covered in the course. It is a good read and a good way to find out the basics of other aspects of AI.

  2. Another useful text book is Computational Intelligence a Logical Approach, David Poole, Alan Mackworth. The book also has a useful home page: http://artint.info/
    Most notably the entire book is available on-line.

Evaluation:

  1. 3 Assignments worth 30% in total (10% each). The assignments will involve programming as well as some written questions. (The programming language used will be python).
  2. Small project worth 15% in total. The project will be team work involving groups of two students.
  3. Midterm Exam worth 15%.
  4. Final Exam worth 40%. The final will be conducted during end of term exam period. You must obtain a mark of at least 40% on the final exam to pass the course.

 

Important Dates (NOTE: assignment dates are projected dates only. There might be some minor shifts in these dates depending on how much progress we make in lectures.

  1. Tuesday 15th Sept. Lectures Start
  2. Tuesday 13th Oct. Assignment 1 due
  3. Tuesday 13th Oct. Assignment 2 handed out.
  4. Thursday 29th Oct. Assignment 2 due.
  5. Monday 2nd Nov. Assignment 3 handed out.
  6. Thursday 5th Nov. Midterm Exam. 1/2 of the class will write at 1:00pm and the other 1/2 will write at 2:00pm
  7. Tuesday 17th Nov. Assignment 3 due.
  8. Tuesday 17th Nov. Mini-Project handed out.
  9. Tuesday 8th Dec. Mini-Project due.
  10. Wednesday 16th Dec. Final exam 9am to 12 noon in rooms SF 3201 and SF 3202