CS/ENGRI 172, Fall 2002: Computation, Information, and Intelligence

8/30/02: Course Information

Knowledge without appropriate procedures for its use is [mute], and procedure without suitable knowledge is blind.
- Herb Simon, "Artificial Intelligence Systems that Understand", 1977.

Course Staff

Prof. Lillian Lee, Upson 4152, , 255-8119
Office hours, September 2nd-13th: M 11:15-12:15 and W 2-3.

Steven Baker, sdb22@cornell.edu
Abraham Heifets, abeh@cs.cornell.edu
Amanda Holland-Minkley, Upson 4116, hollandm@cs.cornell.edu

Time and Place

MWF 10:10-11:00am, Hollister 401

Syllabus

We will be covering a variety of material, ranging from classic material to very recent research results. While we will begin and end with somewhat philosophical material, in general we will focus on technical, mathematically- and computationally-oriented issues.

1. Computation
   
   • Computer problem solving: Deep Blue and computer chess; search techniques; game-playing techniques
   • Learning: neural nets and perceptrons; the nearest-neighbor algorithm
   • Turing machines and the limits of computation
   
   
2. Information
   
   • Information retrieval: Boolean and vector space models; term weighting
   • The World Wide Web: link structures, search algorithms, hubs and authorities; random graph models and power laws
   • Natural language processing: getting computers to understand human languages; formal models of syntax; pushdown automata; discourse; Zipf's law; the Federalist Papers and statistical authorship attribution; machine translation; Japanese word segmentation; statistical language learning in infants
   
   
3. Intelligence
   • The Turing Test; the Chinese Room; the Loebner Prize

References

Not required; on reserve at the Engineering Library, Carpenter Hall.

A very nice book is Richard K. Belew, Finding Out About: A Cognitive Perspective on Search Engine Technology and the WWW (Cambridge University Press, 2001). It discusses a number of the topics we will consider, although the level of presentation sometimes varies (in both directions) with respect to the depth we will explore in lecture.

A classic reference on AI is Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Prentice Hall, 1995, second edition out soon).

Some of our coverage of traditional IR topics is drawn from Bill Frakes and Ricardo Baeza-Yates, Eds., Information Retrieval: Data Structures & Algorithms (Prentice-Hall, 1992).

Enrollment Information

The prerequisite is elementary calculus.

This class satisfies the ENGRI requirement for engineering students. It cannot be used as a substitute for CS100 or CS99. It is not open to students who have completed the equivalent of CS100; if you have questions, please contact the instructor.

Those interested in the material but possessing prior programming experience at the level of CS100 or above may wish to consider taking CS430 (Information Discovery), CS472 (Foundations of Artificial Intelligence), or CS474 (Introduction to Natural Language Processing) upon completion of the appropriate prerequisites. The department also offers a number of related graduate courses.

Course Materials

Lecture is the primary communication point, and attendance (which of course is expected in all Cornell courses) is especially important given that there is no text. Copies of handouts will be available in the racks outside Upson 303. Course policy is that posting of handouts to the class website, http://www.cs.cornell.edu/courses/cs172/2002fa, will lag behind hardcopy distribution in class and at Upson 303, and the right is reserved not to post some handouts online at all. Since hardcopies of the handouts are available at all hours in the Upson 303 racks, this should pose no problem.

Unclaimed homework and exams for which batch return has been permitted will be available in the bins inside Upson 303 during business hours.

Homework and Exams

There will be six problem sets, comprising 60% of the course grade, due at the beginning of class on 9/23, 10/2, 10/9, 10/30, 11/13, and 12/6, and handed out at least a week in advance. Late homework will not be accepted (for emergencies, contact the instructor). There will also be an in-class midterm on October 18 (15% of the course grade) and a comprehensive final exam on Friday, December 20th at 9am (25% of the course grade).

• Collaboration and citation policy: You may discuss homework problems and general solution strategies with each other, but you must develop the details yourself and write up solutions separately without the aid of collaborative notes. Therefore, one student should never have a copy of even part of another student's homework. You are allowed to consult other books, web pages, and so forth, but you must cite your sources if you do so (this includes mentioning who you worked with), and you must write up your answer in such a way as to demonstrate that you understand the solution. This implies that simply copying answers from other sources is not acceptable. When in doubt, ask beforehand!
• Regrade policy: The course staff will grade your work carefully. However, questions about grading do occasionally arise. If so, first read the solutions. If questions persist, please see the grader of that problem (come to office hours or schedule an appointment). In the interests of smooth administration and also to encourage you to look at your graded work soon after it is returned, regrade requests must be made within three weeks of when the work was returned. We reserve the right to make regrade decisions ``off-line'' (i.e., not immediately at the time requested).

Academic Integrity

You are expected to maintain the utmost level of academic integrity in the course, in accordance with the Handbook of Academic Integrity and the homework policies outlined above. It is your responsibility to protect your work from unauthorized access. Again, if in doubt about whether something is allowed, ask beforehand.

Academic dishonesty has no place in a university or anywhere else: it wastes our time and yours, and it is unfair to everyone else. Any violation of this code will be penalized, as we take this issue very seriously.

This document was generated by editing the output of LaTeX2HTML translator Version 2002 (1.62)

Copyright © 1993, 1994, 1995, 1996, Nikos Drakos, Computer Based Learning Unit, University of Leeds.
Copyright © 1997, 1998, 1999, Ross Moore, Mathematics Department, Macquarie University, Sydney.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.