CPE/CSC 480 F03 Artificial Intelligence Syllabus

General Information

• Course Description: [from the Cal Poly 2001-3 Catalog]

"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
  1. know classical examples of artificial intelligence
  2. know characteristics of programs that can be considered "intelligent"
  3. understand the use of heuristics in search problems and games
  4. know a variety of ways to represent and retrieve knowledge and information
  5. know the fundamentals of artificial intelligence programming techniques in a modern programming language
  6. consider ideas and issues associated with social technical, and ethical uses of machines that involve artificial intelligence

Textbooks

The following textbook will be used in this course:

• Artificial Intelligence: A Modern Approach (Second Edition) by Stuart Russell and Peter Norvig;
  Prentice Hall, 2003. ISBN 0-13-103805-2.

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:

• A comparison of AI text books by Stuart Russell and Peter Norvig can be found at http://www.cs.berkeley.edu/~russell/competing.html.
• 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.
• Another AI textbook with an agent-based perspective is Artificial Intelligence: A New Synthesis by Nils J. Nilsson, Morgan Kaufmann, 1998, ISBN 1-55860-467-7.
• 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.
• A more philosophically oriented treatment of the major AI topics is Paradigms of Artificial Intelligence -- A Methodological and Computational Analysis by Achim Hoffmann, Springer-Verlag, August 1998, ISBN 981-3083-97-2.

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.

• Constructing Intelligent Agents with Java: A Programmer's Guide to Smarter Applications. Joseph P. Bigus and Jennifer Bigus, John Wiley & Sons, 1997, ISBN 0-471-19135-3. Paperback/CD-ROM: US49ドル.99
• Intelligent Java Applications for the Internet and Intranets, Mark Watson 1997 Morgan Kaufman (Many Distributed AI examples developed in Java)
• Programming Intelligent Agents for the Internet, Mark Watson McGraw-Hill 1996 (for Windows 95 and NT programmers who want to automate retrieval of information from the Internet).
• AI Agents in Virtual Reality Worlds, Mark Watson J. Wiley 1996 (C++ framework for AI in games)

Lecture Notes

The PowerPoint slides used in class will be available to students from the bookstore, or through this Web page (e.g. via the course schedule).

Additional Material

Further material will be made available through handouts in class, and through pointers to relevant Web pages.

Grading Policy

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.