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| General Info |
| Assessment |
| Materials |
| Textbooks |
| Files |
| Assignments |
| Timetable |
CPSC 433: Artificial Intelligence - Materials
Textbooks
The following is a collection of text books on AI. I recommend that you look at them in the library and decide for yourself which one you find best (i.e. which one explains the best the things that you did not understand in the lectures and labs). They all have a rather large overlap in their content and none of them covers all of the course (in the depth that I want the different topics covered). Note that some of them are out of print (but you might be able to buy used copies cheap). It might also be interesting to compare the rather old books with the newer one (you will see that new means not always better).
- Introduction to Artificial Intelligence - Charniak, McDermott (Addison Wesley), 1985.
- Artificial Intelligence - Second Edition - Rich, Knight (McGraw Hill), 1991.
- Artificial Intelligence: A Modern Approach - Russell, Norviq (Prentice Hall), 1994.
- Artificial Intelligence - Luger (Addison Wesley), 1997.
Files to the course
This file contains two chapters of a book I have written in German and I am in the process of translating it into English. It explains compactly search in general and the search paradigms we will be covering in this course. Note that since the book is not published yet, I have restricted access to computers in the ucalgary domain.
The slides containing the general information on a particular topic that I use in the lectures will be available before the respective lectures here as Acrobat pdf-files (in two formats: one slide per page and the 6 slides per page handout). It is recommended that students take a look at the slides before I go over them in lecture so that they can ask questions and are prepared for the examples we will be going through (they are not completely part of the slides). Note that the pdf-files have been produced using Acrobat 5.0!
| Date | handout format | one slide per page |
|---|---|---|
| Sep. 9 | Introduction | Introduction |
| Sep. 14 | Knowledge Processing - Intro | Knowledge Processing - Intro |
| Sep. 16 | Search: Basic Definitions | Search: Basic Definitions |
| Sep. 21 | Set-based Search | Set-basedSearch |
| Sep. 28 | And-tree-based Search | And-tree-based Search |
| Oct. 7 | Or-tree-based Search | Or-tree-based Search |
| Oct. 14 | Other search models | Other search models |
| Oct. 19 | Search control issues | Search control issues |
| Oct. 21 | Knowledge representation: intro and logic | Knowledge representation: intro and logic |
| Oct. 28 | Knowledge representation: first-order logic | Knowledge representation: first-order logic |
| Nov. 2 | Rule-based Systems | Rule-based Systems |
| Nov. 16 | Frame-based systems | Frame-based systems |
| Nov. 18 | Semantic Nets | Semantic Nets |
| Nov. 23 | Neural Networks | Neural Networks |
| Nov. 25 | Add-ons: constraints | Add-ons: constraints |
| Nov. 30 | Planning | Planning |
| Dec. 7 | Learning | Learning |
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to the assignments of the course. |
Last Change: 30/11/2004