46-927 Introduction to AI

Introduction to Artificial Intelligence, 46-927, Fall Mini #2 1997

Dr. Jill Fain Lehman
School of Computer Science, Carnegie Mellon University


The purpose of this course is to broaden understanding of computational problems and their solutions. Many sorts of problems have well-understood, easily-specified solutions -- a program either solves the problem or it does not. We will continue to explore the properties of such programs by expanding the base of fundamental data structures, algorithms and their uses introduced in the C++ and JAVA mini courses. At the same time, however, we introduce the large class of problems for which we cannot write programs that are guaranteed to find the correct, or even the best solution. Artificial Intelligence (AI) is the area of computer science concerned with developing representations and techniques for finding heuristic solutions to such problems. By exploring the basic data structures in both algorithmic and heuristic settings, we can better understand the gap between what we want computers to do and what we can make them do given realistic constraints on space and time.


Time and Place: Thurs 5:30-8:30, FastLab, GSIA

Instructor:

Jill Fain Lehman (jef@cs.cmu.edu), Doherty Hall 4304, x8-6246

Teaching Assistant:

Jeffrey Stephenson (jeffreys@andrew.cmu.edu), Office hours: Sunday 10:00-noon, FASTLab

Administrative Help:

Pittsburgh: Elizabeth Kelly (eb1k+@andrew.cmu.edu), GSIA 129, 412-268-7358
New York: Yuvelin Tejeda (tejeda+@andrew.cmu.edu), 212-603-3899

Textbooks: There are no required texts for this class. If you wish to read further on topics covered then, depending on the topic, of course, almost any introductory AI, data structures or computational theory text will do. Here are three that you may find useful:

Grading:
Will be based on homeworks (75%) and a final (25%).
Note: you must pass the final to pass the course.

Final Grade Distribution and Explanation

Policy on homework:

Homework Assignments:


Syllabus