Outline: The course will be an introduction to Artificial Intelligence. Artificial Intelligence as studied in Computer Science (and thus as studied in this course) focuses on computational intelligence: trying to understand the computational principles behind intelligent behavior. The central premise thus being that computation is the appropriate paradigm for this task. 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 (Uninformed Search, Heuristic Search, Gametree Search, Backtracking Search).
2. Logical representations and reasoning (First-order logic, Resolution).
3. Classical automated planning.
4. Representing and reasoning with uncertainty (Bayes Net).
5. Decision making (planning) under uncertainty.

Course Textbook (Strongly recommended): Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig. 3rd Edition (the 2nd Edition will do as well). AIMA has a useful home page: http://aima.cs.berkeley.edu/.

We will be covering only material from the Sections I - IV of the book.

[2 copies are on 24hr reserve in the Engineering and Computer Science Library]

Another useful text book is Computational Intelligence a Logical Approach, David Poole, Alan Mackworth, and Randy Goebel, Oxford Press, 1998. The book also has a useful home page:  http://www.cs.ubc.ca/spider/poole/ci.html.

Programming: The Prolog programming language will be used in the course. You are expected to know or to learn enough of the language to complete the course assignments. We will provide a Prolog tutorial the first day of class. Note however that the course is not by and large a programming course. Here is a list of prolog resources and information about running prolog on CDF.

Evaluation:

1. 3 Assignments 15% each. Assignments will be a mixture of programming and theoretical work.
2. 1 Term Test 20%. The test will cover material from the first part of the course. You will be responsible for material covered in lectures, tutorials, your first assignment, and the relevant book chapters (as mentioned in the lecture outline).
3. Final Exam 35%. The exam will cover the entire material of the course. You will be responsible for material covered in lectures, tutorials, assignments, and the relevant book chapters (as mentioned in the lecture outline).
   In order to pass the class a mark of 40% or higher is required in the final exam.
   

Important Dates:

• Mon Sep 12, first class, Prolog tutorial.
• Sun Sep 25, Last day to add the course.
• Mon Sept 19, first lecture, A1 out.
• Mon Oct 10, THANKSGIVING, no class.
• Fri Oct 14, A1 due.
• Mon Oct 17, A2 out.
• Mon Oct 24, In-class test.
• Thu Nov 03, Last day to drop the course.
• Mon Nov 07, FALL BREAK, no class.
• Fri Nov 10, A2 due.
• Mon Nov 14, A3 out.
• Fri Dec 02, A3 due.
• Mon Dec 05, last Monday class.
• Wed Dec 07, make-up class.
• Dec 09 - 20, Exam Period.