Under serious reconstruction: read with care!

This is the home page for the course CS 251: Artificial Intelligence, offered by the Department of Computer Science at the University of Vermont, Fall 2007. (N.B., the content of this page changes frequently.)

Catalog Description:

Introduction to methods for realizing intelligent behavior in computers. Knowledge representation, planning, and learning. Selected applications such as natural language understanding and vision. Prerequisites: CS 103, 104, and STAT 151.

General Information:

• Instructor: Robert R. Snapp, snapp@cs.uvm.edu.
• Office Hours.
• Class meets on Monday, Wednesday, and Friday in Room 367 Votey, 2:30 – 3:40 p.m.

Textbooks:

• Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, second edition, Prentice-Hall, 2003, (known as AIMA.) (Errata, remarks)

• Peter Norvig, Paradigms of Artificial Intelligence Programming , Morgan-Kauffmann, San Francisco 1992, (known as PAIP). (errata, retrospective, and source code)

Handouts:

Most handouts are availabe in pdf format, a page description language supported by Adobe Acrobat. If you do not have Acrobat Reader for your personal computer, you can download it for free from Adobe.

• Syllabus (3 pages).
• nQueens.lisp
• Midterm 1 (due Fri., Oct. 19)[pdf].

Homework Assignments:

• Homework 1: Read Alan Turing's classic article, "Computing Machinery and Intelligence." and Chapters 1 & 2 of AIMA by Friday, August 31, 2007.
• Using ANSI Common Lisp, create a function palindrome? that accepts a single character string as an argument, and returns T if that string is a palindrome, and NIL otherwise. Thus, (palindrome? "Hello World") should return NIL, and (palindrome? "Hello olleH") should return T. Due, Wednesday, September 5, 2007
• Homework 2: Please complete problems 2.4, 2.7, 2.8, 2.9, and 2.10 in AIMA, pp. 57–58. Problems 2.7 through 2.10 should be implemented in lisp. (Note that a partial solution to problem 2.7 appears in the AIMA online code repository. Due Friday, Sept. 14, 2007.Due date extended to Wed., Sept. 19, 2007.
• Homework 3: Please complete problems 4.1, 4.7, 4.10, and 4.16 (8-puzzle only). Your implementations in problems 4.10 and 4.16 should be in lisp. For each, set of experiments, please provide a thorough statistical analysis that includes estimates of the sample means and variances of both the number of node expansions and the overall solution length. (We will compare these in class next week.) Due, Monday, Oct. 8, 2007.

Lecture Notes:

• agents.pdf (5 Sep. 2007)
• clos.pdf (9 Sep. 2002)
• problemsolving.pdf (13 Sep. 2002)
• heuristics.pdf (23 Sep. 2002)
• games.pdf (2 Oct. 2002)

Resources:

General Links

• American Association for Artificial Intelligence (AAAI)
• AI topics
• The ACM SIGART Home Page
• AIXploratorium of the University of Alberta.
• B Course: an on-line tutorial on Bayesian methods.
• Boosting
• CIspace A place to learn about Computational Intelligence.
• CMU AI Repository
• COLT: Computational Learning Theory
• Institute for Information Technology's AI Resources.
• John McCarthy's What is Artifical Intelligence?
• Stuart Russell's AI on the Web

Journals

• Journal of Artificial Intellegence Research (JAIR): a freely accessible electronic refereed journal.
• Journal of Machine Learning Research (JMLR): another freely accessible electronic refereed journal. Click on the target "Papers" to access pdf or postscript versions of published articles.

Lisp Programming

• Association of Lisp Users
• David B. Lamkins, Successful Lisp, bookfix.com, Frankfurt am Main, Germany, 2005.
• Peter Seibel, Practical Common Lisp, Apress, NY, 2005.
• Guy L. Steele's Common Lisp: The Language, 2nd ed.
• The Common Lisp Cookbook, YUMM!
• Paul Graham's web page.
• Marty Hall's Introduction to Common Lisp .
• CMU Common Lisp Repository
• Common Lisp Open Code Collection (CLOCC).
• Common Lisp HyperSpec.

Lisp Implementations

• Allegro CL for Windows, Linux, and FreeBSD: a free demo version from Franz Inc.
• CLISP: a portable ANSI Common Lisp System (download).
• CMUCL Home Page: the new official home of CMU Common Lisp. (This implementation can be run on the EMCF machines using the script at /usr/local/bin/cmulisp.
• Freelisp for Windows or Linux, free demo versions of LispWorks, and Lucid Common Lisp.
• Macintosh Common Lisp (MCL), is available from Digitool, Inc.
• XLISP-STAT is a free lisp interpretor from the University of Minnesota, for Amiga, Macintosh, and Microsoft Windows.

AI Demos

• Chinook, the world's strongest checkers player, which you can play!
• The CHAT Natural Language System
• ELIZAneth, the ``sister'' of Joseph Weizenbaum's ELIZA. Here's an unofficial implementation.
• Jay Scott's page on Machine Learning in Games.
• Marty Hall's Java implementation of the N-Queens Problem.

Data bases

• CMU Face Recognition Data Set
• DELVE: Data for Evaluating Learning in Valid Experiments
• MLnet Machine Learning Archive at GMD
• ORL Database of Faces
• UCI Machine Learning Repository
• National Library of Medicine. Managed by NIH, and contains bibliographic information, as well as GenBank, the NIH genetic sequence database.

Reference Books

• Christopher M. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, Oxford, 1995.
• Margaret A. Boden, ed., The Philosophy of Artificial Intelligence, Oxford University Press, Oxford, 1990.
• Edward A. Feigenbaum and Julian Feldman, Computers and Thought, AIII Press/MIT Press, Cambridge, MA, 1995; originally published by McGraw-Hill, New York, 1963
• Kenneth D. Forbus and Johan de Kleer, Building Problem Solvers, MIT Press, Cambridge, MA, 1993. (source code)
• Paul Graham, ANSI Common Lisp, Prentice-Hall, Upper Saddle River, NJ, 1995, ISBN 0133708756.
• Michael R. Genesereth and Nils J. Nilsson, Logical Foundations of Artificial Intelligence, Morgan-Kaufmann, San Francisco, 1987.
• Daniel Jurafsky and James H. Martin, Speech and Natural Language Processing, Prentice-Hall, Upper Saddle River, NJ, 2000.
• John R. Koza, Genetic Programming, MIT Press, Cambridge, MA, 1992.
• George F. Luger, Artificial Intelligence, Addison-Wesley, Reading, MA, 2002.
• George F. Luger, ed., Computation & Intelligence: Collected Readings, AIII Press/MIT Press, Cambridge, MA, 1995.
• David Marr, Vision, W. H. Freeman, San Francisco, 1982.
• Tom M. Mitchell, Machine Learning, McGraw-Hill, New York, 1997.
• Nils J. Nilsson, Artificial Intelligence: A New Synthesis, Morgan Kaufmann, San Francisco, 1998.
• Nils J. Nilsson, Principles of Artificial Intelligence, Tioga Publishing Company, Palo Alto, CA, 1980.
• Rosalind W. Picard, Affective Computing, MIT Press, Cambridge, MA, 1997.
• Patrick Henry Winston, Artificial Intelligence, Addison-Wesley, Reading, MA, 1984.
• Patrick Henry Winston and Berthold Klaus Paul Horn, LISP, 3rd edition, Addison-Wesley, Reading, MA, 1989.

Intelligent People

• John McCarthy
• Marvin Minsky
• Nils Nilsson