605.451: Principles of Artificial Intelligence, Fall 1998

Lecturer:

Paul McNamee

Textbooks:

• Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall 1995. Required Text.
• Paul Graham, ANSI Common Lisp, Prentice-Hall, 1995 is a great Lisp book, but doesn't have an AI-focus like W&H (below). Optional text

Location:

The class meets Mondays from 7:15 - 10:00pm in room K-8.

Objectives:

This course examines the theory, techniques, and applications of Artificial Intelligence. The course addresses two major areas: representation and reasoning. Topics focusing on representation include symbolic, production rule, and object-based schemes. Topics focusing on reasoning may include weak methods (e.g. path finding, constraint propagation, games, heuristic search), deduction, uncertainty management, non-monotonic reasoning, natural language, machine learning, neural networks, and planning. The languages Common Lisp and Prolog are introduced as a tools for expressing symbolic knowledge. Students who complete this course or those with previous AI / Lisp experience may be interested in 605.452 Artificial Intelligence Programming, a follow-on course that has a theme of developing programming skills appropriate for writing large AI systems (not offered every year).

Schedule of Topics:

September	14	R&N 1-3	Representations, State Space Search
September	21	Handout, R&N 4	Heuristic Search
September	28	Handout, R&N 5	Linear Space Heuristic Search, Game Playing
October	5	Handout, W&H 1-4	Introduction to Lisp
October	12	Handout, W&H 5,7	Lisp and Symbolic Manipulation
October	19	Handout, W&H 6	Lisp and Recursive Programming
October	26	R&N 22	Natural Language: Grammars, Parsing
November	22	R&N 22	Information Retrieval, Midterm Exam
November	9	R&N 6,7	Propositional and First Order Logic
November	16	R&N 9	Logic and Theorum Proving, Introduction to Prolog
November	23	Handout, R&N 10	Logic Programming and Prolog
November	30	R&N 11,12	Expert Systems and Rule-Based Programming
December	7	Handout	Overview of Neural Networks
December	14	Handout, R&N 19	Reasoning with Uncertainty

Coursework:

Coursework will be a combination of weekly assignments, midterm and final exams, and a research paper / project. Homework will be a mix of problems and small programing assignments which are designed to reinforce the material covered in lectures and the reading. The lowest grade on the homework assignments will be dropped and students with an `A' average for the course will not be required to take the final exam. In general, late work will not be accepted unless I am contacted before the material is due. You are primarily responsible for the material covered during lectures but should also read the chapters in the text and the assigned handouts.

Ethics:

Work for this class is expected to be the result of individual effort. It is perfectly acceptable to make use of published examples and code in the literature with attribution. Furthermore, while it is permissible to discuss the general nature of lecture material and assignments with your peers, this does not extend to revealing solutions or source code. Uphold the academic integrity of the university. Students using without reference, published material or copying another's work will receive an `F' on the assignment and the matter will be referred to the dean. If you have any questions about this policy or any other questions about an assignment, contact me during the week.

Homeworks:

1. HW #0: Apply for a UNIX account right away and send me email.

Handouts:

1. Search Overview handout.
2. Korf Search Summary Paper.
3. Samuel's Checking playing and Machine Learning paper.
4. Scientific American Computer Chess article.
5. Lisp Handouts (many of these are from material provided by Marty Hall):
   • Lisp Overview.
   • Conditional Expressions.
   • Let / Let* and Progns.
   • Loop.
   • Higher Order Functions.
   • Structures

Lisp Resources:

• Marty Hall's Lisp Page, here at Hopkins, is an unsurpassed, on-line reference for Lisp programmers.
• Common Lisp the Language, 2nd Edition, Digital Press, 1990. For many years this was the language reference while / before ANSI standardization. This on-line version of the book is a great "bookmark" for looking up the syntax of different commands.
• Franz Inc. is a commercial lisp vendor who offers a free, limited Lisp compiler, Allegro CL Lite, for Windows.
• Harlequin is a commercial lisp vendor who offers a free Lisp product, FreeLisp, a simplied version of their LispWorks product for Windows. Harlequin's Lisp is the one available here on the JHU system.
• Lisp FAQ (comp.lang.lisp)
• Association of LISP Users (ALU)
• Though its not a text for the course, Patrick Henry Winston and Berthold Horn's, LISP 3rd edition, Addison Wesley, 1989 is a book I've used in previous courses. It's a good reference if you find Graham difficult and want a simpler Lisp introduction. The source code is available from my home directory in: 451/lisp/winston-horn/.
• Source code from some other Lisp texts is also available:
  • 451/lisp/graham/ (Graham's ANSI Common Lisp).
  • 451/lisp/norvig/ (Peter Norvig's PAIP).

Prolog Resources:

• AMZI's good, free Prolog for Windows I haven't tried it myself, but I hear that this is a very good Prolog development environment that comes with an excellent tutorial.
• Yahoo Prolog site. This site contains links to the comp.lang.prolog FAQ and other resources.
• XSB Prolog. You can get a free Prolog-like interpreter here. This is the prolog used in the class on the UNIX system.

FTP Sites:

• Common Lisp Repository at Carnegie Mellon. (Note: you can get CLIPS here)
• Source Code to Peter Norvig's Paradigms of AI Programming This is a local copy. The original came from anonymous ftp at unix.sri.com.
• CLOS Repository, etc...
• SCREAMER: A Non-Deterministic Logic Substrate in Common Lisp

AI Sites / Resources:

• MIT AI Laboratory
• Stanford AI Laboratory
• SIGART, The Association for Computing Machinery's Special Interest Group on AI
• JHU AI Page. Resource describing faculty and ongoing research at Homewood.
• AI Attic Repository (at UTexas)
• American Association for Artificial Intelligence (AAAI) This is the sponsoring orgainization for the National Conference on AI.
• Newsgroup: comp.ai This group has a pretty high noise-to-signal ratio, but covers all facets of AI. More groups exist for specialized topics such as comp.ai.neural-nets.
• Local AI seminar series given by the Navy Center for Applied Research in AI which are open to the public. Talks are at 10:00am on Mondays.

JHU on-line resources

• The Johns Hopkins University's Computer Science Department. (at the Homewood campus).
• The Whiting school's part-time program in Computer Science home page.
• The Milton S. Eisenhower library at the Homewood campus is a good source for AI texts (it has a much larger selection than the Gibson library) and is a quiet place to study since it is open until midnight. The library's electronic card catalog (JANUS) is available on-line via telnet.
• The Gibson library (located on the APL campus) also has an on-line card catalog.
• A CGI interface to the UNIX man pages is on-line.