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

CS 480 Introduction to Artificial Intelligence


Meeting time: Tuesday 4:30 pm – 7:10 pm

Meeting location: Innovation Hall 206


Instructor: Dr. Gheorghe Tecuci, Professor of Computer Science

Office hours: Tuesday 7:15 pm – 8:15 pm
Office: Nguyen Engineering Building 4613
Phone: 703 993 1722
E-mail: tecuci at gmu dot edu


Teaching Assistant: Mr. Muzammil Sagheer

Office hours: Wednesday 3:30 pm – 4:30 pm
TA Office: Nguyen Engineering Building 4456

E-mail: msagheer 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, logic and probabilistic reasoning, learning and knowledge acquisition, knowledge engineering, expert systems and intelligent agents, Common LISP and Prolog. The students will also learn about the Disciple agent development environment created in the Learning Agents Center of George Mason University.


Students will have accounts on Blackboard and can download the PDF slide files by going to and logging in using their Mason ID and passwords.




Students will obtain a basic understanding of uninformed and heuristic search techniques, of basic logic and probabilistic reasoning techniques, and of basic machine learning techniques. Students will obtain the ability to implement basic AI methods in Lisp, Prolog or a knowledge-based systems development environment, and will have the ability to identify and apply basic AI methods to a given problem.


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: 10/26/2010

Final exam: 12/14/2010


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

GMU is an Honor Code university. 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. We reserve the right to use MOSS to detect plagiarism in the programming assignments.

Required Readings


Tecuci G., Lecture Notes in Artificial Intelligence, 2010 (available online).


Recommended Readings


Russell S., and P. Norvig P., Artificial Intelligence: A Modern Approach, Prentice Hall, Third edition (ISBN-13: 978-0-13-604259-4, 2010) 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.


Poole D.L. and Mackworth A.K., Artificial Intelligence: Foundations of Computational Agents, Cambridge University Press, 2010.


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.


Jones T.M., Artificial Intelligence: A Systems Approach, Jones and Bartlett Publishers, 2009.


Luger G., Artificial Intelligence: Structures and Strategies for Complex Problem Solving, Addison Wesley, 2009.


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, 2010

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; production systems; probabilistic reasoning; semantic web and ontologies; planning; problem solving agents) 

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

Common Lisp, Prolog and Disciple


Email Communication

1. Please include CS480 in the subject of any message you are emailing to Dr. Tecuci.

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


GMU Email Accounts

Students must activate their GMU email accounts to receive important University information, including messages related to this class.


Office of Disability Services

If you are a student with a disability and you need academic accommodations, please see me and contact the Office of Disability Services (ODS) at 993-2474. All academic accommodations must be arranged through the ODS.


Other Useful Campus Resources

Writing Center: A114 Robinson Hall; (703) 993-1200;

University Libraries “Ask a Librarian”

Counseling And Psychological Services (CAPS): (703) 993-2380;


University Policies

The University Catalog,, is the central resource for university policies affecting student, faculty, and staff conduct in university affairs.