George Mason University
School
of Information Technology and Engineering
Department of Computer Science

CS 580 Introduction to Artificial Intelligence

 

Meeting time: Wednesday 7:20 pm 10 pm

Meeting location: ST I 126

 

For current information on this course go to: http://lac.gmu.edu/cs580-fa07/cs580-tecuci-g.htm

 

Instructor: Dr. Gheorghe Tecuci, Professor of Computer Science

Office hours: Monday 5 pm 6 pm
Office: Research I Building, Room 436
Phone: 703 993 1722
E-mail: tecuci at gmu dot edu

 

Teaching Assistant: Ms. Nada A. Basit

Office hours: Tuesday 5 pm 6 pm

Office: S&T II building, Room 437

Email: nbasit at gmu dot edu

 

 

Course Description

 

Artificial 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 and Prolog. The students will also learn about and use the Disciple agent development environment created in the Learning Agents Center of George Mason University.

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/.

 

Grading Policy

 

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%

 

Exam Dates

 

Mid-term exam: 10/17/2007

Final exam: 12/12/2007

 

Lateness Policy

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

You are expected to abide by the University's honor code. Any collaboration between students on assignments or exams is unacceptable. If it is determined that two assignments or exams have not been done independently, then the grade will be split between their authors. For example, in case of a 30p assignment each will receive 15p. Note that we will use MOSS to detect plagiarism in the programming assignments.

Required Readings

 

Tecuci G., Lecture Notes in Artificial Intelligence, 2007, available online (see outline below).

 

Recommended Readings

 

Russell S., and P. Norvig P., Artificial Intelligence: A Modern Approach, Prentice Hall, Second edition, ISBN: 0-13-790395-2, 2003. 

 

Graham P., ANSI Common Lisp, Prentice Hall, ISBN: 0133708756, available on line.

 

Other Useful Readings

 

Tecuci G., Building Intelligent Agents: An Apprenticeship Multistrategy Learning Theory, Methodology, Tool and Case Studies, Academic Press, 1998.

 

Giarratano J. and Riley G., Expert Systems: Principles and Programming, Third Edition, PWS Publishing Company, Boston, 1994.

 

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.

 

Bratko I., PROLOG Programming for Artificial Intelligence, Addison Wesley.

 

Coppin B., Artificial Intelligence Illuminated, Jones and Bartlett publishers, 2004.

 

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, 2007

Overview of Artificial Intelligence and Intelligent Agents

Solving Problems by Searching (state-space and problem reduction representations; uninformed search; informed search; constraint satisfaction problems; adversarial search)

Knowledge Representation and Reasoning (logic; natural deduction; resolution; prolog; production systems; probabilistic reasoning; semantic web and ontologies; planning; problem solving agents) 

Machine Learning and Knowledge Acquisition (learning strategies: version spaces, decision trees, instance-based, case-based, explanation-based, analogical, multistrategy; problem solving and learning agents)

Common Lisp

 

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; 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 production NEW client runs on Windows (2000, XP and Vista) and Linux systems, with a client under development for Macintosh. All versions provide the instructor's voice and graphics in real time, and have 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 (without video), but it must not be overloaded at class time or the sound delivery will be unacceptable and you are likely to be cut off automatically. 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 NEW 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". Your username and password for NEW will be the same as for your GMU email.

Instructions for using GMU dialup are available at: http://itusupport.gmu.edu/STG/dial-up.asp

If you have not previously installed NEWv4.2.4 you will need to download it.

Login and click on the top bullet of the Welcome to NEW page (Download/install Software), then 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, else 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 problems with NEW, send email to disted@netlab.gmu.edu

 

Final remarks

1. Please include CS580 in the subject of any message you are emailing to Dr. Tecuci (otherwise he may not read it).

2. Please try to limit the size of the files you are emailing.

3. If you are a section 2 (Internet) student, you can either mail the assignments to Dr. Tecuci by the indicated deadline, or scan and email them both to Dr. Tecuci and Ms. Basit (again making sure that the files are not too large).

4. The mail address of Dr. Tecuci is:

Prof. Gheorghe Tecuci

MSN 6B3, George Mason University

4400 University Drive, Fairfax, VA 22030-4444