Fall 1998 308-424A: Topics in Artificial Intelligence
Tentative Lecture Plan
Here, I list all important known dates of course lectures,
assignments, tests and so on. This includes lectures that have
already happened and the planned lectures and events in the near
Note to people outside McGill. Feel free to use the
slides and materials available online here. Please email Gregory
to let him know you're using them, and comments and corrections
are always greatly appreciated.
On PDF format: Most notes will be provided using Portable
Document FORMAT (PDF) files. The reader for PDF
files is available free from Adobe for UNIX, Macs, and Windows.
PDF files can also be viewed using ghostscript.
- Tuesday Sept 2: A handout
of administrative course details and a
quick overview of Artificial Intelligence
- Thursday Sept 7: overview of Artificial
Intelligence (cont'd) Notes from the lecture
slides are slightly different from the on-line overview.
[PDF file: more
- Sept 9: lectures 3&4 were on Knowledge Representation.
Assigned: Read chapters 6 & 7 in the text.
Slides from lecture 3 are available
as PDF as well as the following key
ideas on CNF in HTML.
- Sept 14: Lecture 4: that disaster where the facy equipment
all failed to work. Notes with general points are available
in PDF form. Additional more detailed notes used for overheads
in lectures 3 &4 are also available. Try the annotated
PDF form, and if that doesn't work for you try the version
with embedded fonts.
The silly Montreal student example
is also available.
- Sept 16: Assignment 1. Using Prolog for theorem
proving. Lists in Prolog. Notes
from lecture 5 in PDF.
- Sept 21/23: Search part1 and part2.
Depth-fist search (DFS), BFS, the use of heuristics & the
We also discussed non-monotonic & default logic (from ch.
- Sept 28: Conclusion of blind search, discussion of chess
and Deep Blue, informed search.
- Sept 30: Informed search (assignment
2 was briefly described)
- Oct 5 : Advanced knowledge rep. Game
playing and adversary search.
- Oct 7: Mid -term test.
- Oct 12:
Introduction to machine learning, symbolic learning, robot perception.
- Oct 14 & 19:
symbolic learning & version spaces
- Oct 21:
symbolic learning, decision trees. Alvinn video.
- Oct 28 & Nov 2 optimizing
of decision trees, non-symbolic learning (neural nets)
- Nov 9 neural networks and backpropagation of error [notes]
- Nov 11 learning case studies (nettalk, alvinn) [notes]
- Nov 16 Midterm, nettalk, glovetalk (&video), wrapup on supervised
neural nets [notes]
- Nov 18 Kohonen nets & unsupervised learning, intro to planning
- Nov 23 Planning and configuration space [notes
(1up for on screen) (2up
- Nov 30-ish Computer Vision [color 1up notes (for on-screen);
b&w 2up notes
- Dec 1 Computer Vision & psychology of vision
- Nov 26: Computer Vision [notes]