Department of Computer Science
CS 580 Introduction to Artificial Intelligence
Meeting time: Monday 4:30pm – 7:10pm
Meeting location: ST I 126
Remark: The lecture notes and the assignments are available through the NEW system
Instructor: Dr. Gheorghe Tecuci, Professor of Computer Science
Monday 3:30 pm – 4:20 pm
Office: Research I, Room 436
Phone: 703 993 1722
E-mail: tecuci at gmu dot edu
Teaching Assistant: Mr. Keith Sullivan
Email: ksulliv at cs dot gmu dot edu
Office hours: Tuesday 3:30pm - 4:30pm and Wednesday 3:30pm - 4:30pm
Office: Research I, Room 470
Intelligence is the Science and Engineering domain which is concerned with the
theory and practice of developing systems that exhibit the characteristics we
associate with intelligence in human behavior such as reasoning, planning and
problem solving, learning and adaptation, natural language processing, and
perception. This course presents the basic principles and the major methods of
Artificial Intelligence, preparing the students to build complex systems
incorporating capabilities for intelligent processing of information. Covered
topics include: heuristic search and game playing, knowledge representation and
reasoning, problem solving and planning, learning and knowledge acquisition,
knowledge engineering, expert systems and intelligent agents, Common LISP. The
students will also learn about the Disciple agent development environment
created in the Learning Agents Center of
This course is delivered to the Internet section online by Network EducationWare (NEW). Students in all sections have accounts on NEW and can play back the lectures and download the PDF slide files at http://disted.ite.gmu.edu.
There will be several homework assignments, a mid-term exam and a final exam.
The course grade will be determined as follows:
Assignments or project 33.3%
Mid-term exam 33.3%
Final exam 33.3%
Mid-term exam: 10/23/2006
Final exam: 12/18/2006
Each assignment should be received by the day indicated as the deadline of the assignment. Any delay will be penalized with 15%/day.
Objective cases of delay will be considered individually, and are not subject to the above policy. An example of such a case is a longer business trip that privents one to return the assignment in time. In such cases permission from the instructor should be requested before the deadline.
Honor Code Policy
Everyone has to do the assignments and the exams by himself or herself. If it is determined that two assignments or exams are too similar to have been done independently, then the grade will be split between their authors. For example, in case of a 30p assignment each will receive 15p.
Tecuci G., Lecture Notes in Artificial Intelligence, 2006, available online (see outline below).
Russell S., and P. Norvig P., Artificial Intelligence: A Modern Approach, Prentice Hall, Second edition, ISBN: 0131038052, 2003.
Graham P., ANSI Common Lisp, Prentice Hall, ISBN: 0133708756, available on line.
Giarratano J. and Riley G., Expert Systems: Principles and Programming,
Third Edition, PWS Publishing Company,
Tecuci G., Building Intelligent Agents: An Apprenticeship Multistrategy Learning Theory, Methodology, Tool and Case Studies, Academic Press, 1998.
Wilensky R., Common LISPcraft, Norton & Company, 1989.
Winston P.H., Artificial Intelligence, Addison-Wesley.
Winston P.H., Horn B.K.P., LISP, Addison-Wesley.
Luger G., Artificial Intelligence: Structures and Strategies for Complex Problem Solving,
Addison Wesley, 2002.
Rich E., Knight K., Artificial Intelligence, McGraw-Hill.
Coppin B., Artificial Intelligence
Illuminated, Jones and
Dean T., Allen J., Aloimonos Y., Artificial Intelligence: Theory and Practice, The Benjamin/Cummings Pub. Comp.
Ginsberg M., Essentials of Artificial Intelligence, Morgan Kaufmann.
Negnevitsky M., Artificial Intelligence: A Guide to Intelligent Systems, Addison Wesley, 2002.
Steele G.L., Common Lisp the Language, 2nd Edition.
G. Tecuci, Lecture Notes in Artificial Intelligence, 2006
Overview of Artificial Intelligence and Intelligent Agents
Solving Problems by Searching (uninformed search; informed search; constraint satisfaction problems; adversarial search)
Knowledge Representation and Reasoning (logic; natural deduction; resolution; prolog; production systems; probabilistic reasoning; semantic networks and ontologies; planning; problem solving agents)
Machine Learning and Knowledge Acquisition (learning strategies: version spaces, decision trees, instance-based, explanation-based, analogical, neural networks, multistrategy; problem solving and learning agents)
Information on the synchronous (real-time) Internet delivery of the course
You also will find the following information and much more on webpage http://disted.ite.gmu.edu.
Terms of Internet attendance: all students have the option to attend every class, but not take the exams, over the net (I will schedule a larger room if needed for the exam); Internet students are expected to attend all classes and may come to the classroom if there is space; all registered students can replay the recordings we make of every class.
The distance education software we will be using is called Network EducationWare (NEW). It consists of a collection of open source tools, integrated using software developed at GMU by Dr. Mark Pullen and his students. You can learn more at http://netlab.gmu.edu/NEW. At present the NEW client runs only on Windows computers (Windows 98, ME, NT, 2000, and XP). It provides the instructor's voice and graphics in real time, and has an option for video if you have high-capacity Internet service such as cable modem or DSL. If you have a microphone that works with your computer's sound setup, you can ask spoken questions during class, even with only a dialup connection.
Before you attend a class over the network, you will need to install the NEW client software and check that (1) it works on your computer and (2) your Internet connection is good enough to support real time class delivery. To be good enough, it does not have to be high capacity; 56k modem service is enough, but it must not be overloaded at class time or the sound delivery will be unacceptable. Because the Internet carries more load in afternoon and early evening, you need to test at those hours. If the sound quality is poor, you have the option to use a dial-up connection to GMU (703-426-2468) with your GMU username and password (as used on OSF1). The software is available online and includes a recorded introduction that runs on the client and can be used to test your Internet connection. If you have trouble with the installation, look on the webpage http://disted.ite.gmu.edu under "Help/FAQs". You also will find a button on http://disted.ite.gmu.edu to get the password you will need with the NEW system. The password then will be sent to your GMU email account.
You will need to download the updated clients of NEWv4.0 unless you loaded them in the Spring 2005 semester. Click on the top bullet of the Welcome to NEW page (Download/install Software) and follow directions.
With most browsers, the load procedure requires you to save (not open) the first file; you then click on it to unzip automatically, and it downloads after you click to approve.
You should not connect for live classes more than 10 minutes before class, because the server will shut down all connections between class sessions.
Please note that normal communication with Internet students is via their GMU email accounts. If you receive your email elsewhere, we suggest you arrange to have GMU email forwarded. (If you do this, you still should check your GMU mailbox occasionally or it may exceed quota, causing email rejections.)
We are looking forward to another successful semester of distance education with the NEW system. If you have questions about your course, ask your instructor. If you have problems with NEW, send email to firstname.lastname@example.org.