"Programs and techniques that characterize artificial intelligence. Programming in a high level
language. 3 lectures, 1 laboratory. "
Prerequisites:
CSC 103 (Fundamentals of Computer Science III)
and CSC 141 (Discrete Structures I)
Students should be familiar with programming in Java,
and be able to work with elementary logic in propositional
and predicate calculus environments.
Goals and Objectives
The goal of this course is to understand important problems, challenges,
concepts and techniques from the field of Artificial Intelligence.
In order to achieve this, students learn how to analyse, design, and
program intelligent agents of varying complexities. These agents gather information
from their environment, convert it into a suitable internal representation
(which may be augmented with information provided by the designer),
analyse their internal knowledge to determine suitable actions,
and finally execute some actions.
More specifically, after successfull completion of the course, students should
know classical examples of artificial intelligence
know characteristics of programs that can be considered "intelligent"
understand the use of heuristics in search problems and games
know a variety of ways to represent and retrieve knowledge and information
know the fundamentals of artificial intelligence programming techniques
in a modern programming language
consider ideas and issues associated with social technical,
and ethical uses of machines that involve artificial intelligence
There is a column in the course schedule
indicating the chapters in the book that
correspond to a topic discussed in class.
Students are expected to read the respective chapters before
the topic is covered in class.
For further reading, here are some more suggestions:
The lecture notes from
MIT's course on Artificial Intelligence
are available through their OpenCourseWare project at
ocw.mit.edu.
The topics covered are similar to ours, and some of the notes
contain nice examples.
The fourth edition of "Artificial Intelligence - Structures and
Strategies for Problem Solving"
by George F. Luger ,
Addison Wesley, 2002, ISBN 0201-64866-0
is based on a more traditional approach to AI, with less emphasis
on intelligent agents.
There are also a few books on more practical aspects of AI programming and
intelligent agents; many of them, however, suffer from a somewhat
cursory treatment of important issues, and are also a little out of date.
The following table gives an overview of the calculation of the grades.
I reserve the right to change the formula used.
Please note that the project consists of several parts which will be evaluated separately.
The project will also be done in teams, and the performance of the team as a whole
will be graded unless there is a clear disparity in the contribution
of the individual team members.
Should this be the case, I might ask for additional documentation like work sheets,
email messages, or draft copies of documentation to evaluate individual contributions.