Artificial Intelligence (CS 07.450 1 - undergraduate)
Concepts in Artificial Intelligence (CS 07.550 1 - graduate)
Spring 2009
Rowan University


Instructor: Dr. Nancy Tinkham
Office: Computer Science Department, Robinson
Phone: 256-4806(office)
E-Mail: nlt@elvis.rowan.edu
Web: http://elvis.rowan.edu/~nlt
Office Hours: Tuesday & Thursday 10:00-12:00; and by appointment
If I am not in meetings, I am usually also in the office during the open period, Wednesday 11:00-12:15.

Class meeting times:

Tuesday & Thursday:  12:15-1:30, Education 2097
Text:
Luger, Artificial Intelligence: Structures and Strategies for Complex Problems Solving, 6th edition, ISBN 0-321-54589-3 (required)
Clocksin & Mellish, Programming in Prolog, 5th ed., ISBN 3-540-00678-8 (recommended)
Grading:
Homework: 25%
Semester project: 30%
Exam 1: 15%
Exam 2: 15%
Final Exam: 15%
Homework and exam policy:

Grade points will be deducted for late homework at the rate of 5 points per weekday.  (For example, a homework assignment that is due on Wednesday and received the following Monday will receive a maximum grade of 85.)

Some of the homework assignments will be paper-and-pencil, and others will be programming assignments. In addition to the smaller programming assignments, there will be a semester project, in which you will be writing a large program in a programming language of your choice. Some assignments will be individual assignments; in others, you will be allowed to work in groups. See the individual assignments for details.

Programs will be graded not only on correctness but also on style and on the quality of the solution.

Prerequisites:
  1. Foundations of Computer Science (CS 07.210)

    You should be comfortable with propositional logic and formal grammars, and you should be familiar with first-order predicate logic.

  2. Data Structures (CS 04.222) or Data Structures for Engineers (CS 04.225)

    You should be comfortable programming in a high-level language, including the use of trees, lists, and recursion. Knowledge of Java or C++ is not required. Knowledge of Prolog is helpful but is not required.

  3. Discrete Structures (MATH 03.160) or Discrete Math (MATH 03.150)

    You should have the mathematical maturity that comes from completing a Discrete Structures or Discrete Math course. You should also be familiar with trees, graphs, sets, and relations.

  4. You will need some familiarity with the UNIX operating system for the Prolog programming portion of the course -- how to use one of the editors, how to print files, and how to do basic file management (copying files, creating directories, and so on). If you have never used UNIX before, see me and I will recommend some references.

Course Topics:

Basic tools for AI problem solving: Knowledge representation (including the predicate calculus), state space search, heuristic search.

One language for AI problem solving: Prolog.

Application areas, including: Puzzle-solving, game-playing, theorem-proving, expert systems, natural language processing, learning and inference (including genetic algorithms).

University Policies:

You should be familiar with these university policies:
Rowan University Attendance Policy
Rowan University Academic Integrity Policy

Graduate Students:

Graduate students taking this course as CS 07.550 will be expected to do more work than is required of the undergraduate students.
  1. The semester project will be held to a higher standard of excellence. The program should accomplish more than would be expected of an undergraduate program, and the elegance of code and clarity of documentation should be at a graduate student level.

  2. As part of the homework grade, graduate students will be expected to give one hour-long talk in class on an AI topic that is not listed in the regular schedule of readings. The topic and date of the talk are chosen by the student, in consultation with the instructor. Possible ideas for the talk include an introduction to genetic algorithms, an introduction to neural networks, a method of inexact or probabilistic reasoning not covered in class, or an approach to natural language understanding not covered in class.

  3. The exams will include extra questions that are extra credit for undergraduates but required for graduate students.


Nancy Tinkham
Computer Science Department, Rowan University

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