CSE 3402 Introduction to Concepts of Artificial Intelligence
Winter 2009
Department of Computer Science and Engineering,
York University
Course Description
This course is an introductory exposition to topics in Artificial
Intelligence (AI). It covers, in some depth, some core subjects of
current research and deployed applications in AI: search, knowledge
representation, reasoning, intelligent agents and their modeling,
acting and planning, neural networks, and genetic algorithms. Other
important subareas of AI, such as robotics or computer vision, are
discussed in depth in other courses.
What's New
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May 21: Assignment 3 may be submitted without penalty until Monday May
25 at 5pm. Hand it in by submitting electronically and dropping a
hardcopy off in the drop box outside CSE 1003.
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May 7: Assignment 3 is out; it is due
on May 21..
Use this Golog interpreter.
See also this elevator controller
example Golog program.
Note that you should change the extensions from .swipl to .pl
before you load the files into SWI Prolog.
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April 15: Assignment 2 is out; it is due
on May 4 - Deadline extended!.
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April 13: Here are some sample questions for the midterm test.
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April 8: The midterm test will be held on April 15. It covers all
the material seen up to and including Week 5 Backtracking Search.
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March 30: Assignment 1 is out; it is due
on April 13.
- Classes start March 4.
Instructor
Prof. Yves Lespérance
Office: CSEB 3052A
Tel: 736-2100 ext. 70146
Email: lesperan "at" cse.yorku.ca
Lectures
Monday, Wednesday, and Friday from 14:30 to 15:30 in TEL 0007.
Instructor Office Hours
Monday, Wednesday, and Thursday 11:00-12:00.
Textbook
Russell, S.J. and Norvig, P.,
Artificial Intelligence: A Modern Approach, 2nd edition
Prentice Hall, 2003.
The textbook is required; it is available at the York University
Bookstore.
Prerequisites
AK/AS/SC/COSC 3401 3.0 or AK/AS/SC/CSE 3401 3.0; AK/AS/SC/MATH 1090 3.0.
Knowledge of Prolog and first-order logic.
Evaluation
| Assignements (3 @ 10% each) | 30% |
| Midterm test | 25% |
| Final exam | 45% |
| Total | 100% |
Tentative Schedule
- Week 1 (Mar 4) Introduction & intelligent agents (R&N ch. 1 & 2).
- Week 2 (Mar 9) Uninformed search (R&N ch. 3).
- Week 3 (Mar 16) Informed search (R&N ch. 4).
- Week 4 (Mar 23) Game/Adversarial Search (R&N ch. 6).
- Week 5 (Mar 30) Constraint satisfaction and backtracking search (R&N ch. 5).
- Week 6 (Apr 6) Logical representations (R&N ch. 7 & 8).
- Week 7 (Apr 13) Inference in first-order logic (R&N ch. 9).
- Week 8 (Apr 20) Reasoning about action (R&N ch. 10, sec. 3).
- Week 9 (Apr 27) Planning (R&N ch. 11, secs. 1, 2, & 4).
- Week 10 (May 4) Uncertain Reasoning (R&N ch. 13-14).
- Week 11 (May 11) Machine Learning.
- Week 12 (May 20 & 21) Review.
Readings and Lecture Transparencies
- Week 1 (Mar 4) Introduction & intelligent agents
Required Readings: Russell & Norvig Chapter 1 & 2.
Lecture transparencies for Russell & Norvig Ch. 1,
lecture transparencies for Russell & Norvig Ch. 2,
instructor's lecture transparencies on Agents and MAS
.
- Week 2 (Mar 9) Uninformed Search
Required Readings: Russell & Norvig Chapter 3.
Lecture transparencies part 1,
lecture transparencies part 2.
- Week 3 (Mar 16) Informed Search
Required Readings: Russell & Norvig Chapter 4, Sec. 1 to 3.
Lecture transparencies.
- Week 4 (Mar 23) Game Tree Search
Required Readings: Russell & Norvig Chapter 6, Sec. 6.1, 6.2, 6.3, and 6.6.
Lecture transparencies.
- Week 5 (Mar 30) CSP and Backtracking Search
Required Readings: Russell & Norvig Chapter 5.
Lecture transparencies.
- Week 6 (Apr 6) Knowledge Representation & First-Order Logic
Required Readings: Russell & Norvig Chapter 8 (Chapter 7 is optional).
Lecture transparencies.
- Week 7 (Apr 13) Inference in First-Order Logic
Required Readings: Russell & Norvig Chapter 9, Sec. 1, 2, and 5.
Lecture transparencies.
- Week 8 (Apr 20) Reasoning about Action
Required Readings: Russell & Norvig Chapter 10 Sec. 3.
Main lecture transparencies,
lecture transparencies from Brachman and Levesque.
- Week 9 & 10 (Apr 27 & May 4) Planning
Required Readings: Russell & Norvig Chapter 11, Sec. 1, 2, and 4.
Lecture transparencies.
- Week 11 (May 11) Reasoning under Uncertainty
Required Readings: Russell & Norvig Chapter 13, and Chapter 14 Sec. 1 and 2.
Lecture transparencies from Brachman and Levesque.
Additional References
A good Prolog text:
Clocksin, W.F. and Mellish, C.S.,
Programming in Prolog, (5th edition), Springer Verlag, New York, 2004.
Other good AI textbooks:
Poole, D., Mackworth, A., Goebel, R.
Computational Intelligence, A Logical Approach,,
Oxford University Press, New York, 1998.
Nilsson, N.J.,
Artificial Intelligence: A New Synthesis,,
Morgan Kaufmann, San Francisco, 1998.
On knowledge representation:
Ronald J. Brachman and Hector J. Levesque,
Knowledge Representation and Reasoning,
Elsevier/Morgan Kaufmann 2004, ISBN 1-55860-932-6
Baral, C.
Knowledge representation, reasoning, and declarative problem solving.
Cambridge University Press, Cambridge/New York, 2003.
Genesereth, M.R. and Nilsson, N.J.
Logical foundations of artificial intelligence.
Morgan Kaufmann, Los Altos, CA, 1987.
On reasoning about action:
Reiter, R.,
Knowledge in Action: Logical Foundations for Specifying and Implementing
Dynamical Systems,
MIT Press, 2001.
York Library eCopy,
Book home page.
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Running SWI-Prolog in the Prism Lab
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To run Prolog execute the command pl. To exit enter
<CTRL>-D
at the prompt.
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Documentation is available
on the web.
Getting Prolog
About Prolog