George Mason University
Volgenau School of Engineering
Department of Computer Science


CS 580 Introduction to Artificial Intelligence

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

Meeting location: Nguyen Engineering Building 4457


Instructor: Dr. Gheorghe Tecuci, Professor of Computer Science and Director of the Learning Agents Center

Instructor office hours: Monday and Thursday 7:15 pm – 8:15 pm

Office: Nguyen Engineering Building 4613

Phone: 703 993 1722

E-mail: tecuci at gmu dot edu

Teaching assistant: Tanwistha Saha, PhD Student, tsaha at masonlive dot gmu dot edu

Teaching assistant office hours: Tuesday, 3pm – 4pm


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, concepts, and 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, semantic web, 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 lecture notes by going to and logging in using their Mason ID and passwords.


Internet Class Delivery:

This course will also be delivered to the Internet section online using the Moodle learning management system with MIST/C, which has replaced the Network EducationWare (NEW) delivery system. Only students in the online section will be able to connect to class sessions and to download recordings of the lectures. All distance learning students are expected to actively participate in the classroom discussions, and will be required to deliver all the assignment by email (see below). The Moodle URL for CS department courses is at The procedure for installation is:

1.      Connect to:  

2.      Select your course and login with your GMU username/password

3.      Enter the enrollment key for your course

4.      Install MIST/C client


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 33.3%

Mid-term exam 33.3%

Final exam 33.3%


Exam Dates

Mid-term exam: 03/22/2012

Final exam: 05/10/2012


Lateness Policy

Each assignment should be received by the day indicated as the deadline of the assignment. Any delay may 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, Spring 2012 (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.

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, 2012

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) 

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

Knowledge-based Agents (architecture, hybrid knowledge representation, knowledge-based reasoning, learning, development methodology)

Common Lisp, Prolog, and Disciple


Email Communication

1. Please include CS580 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.

3. If you are in the distance education section, you may email the assignments to Dr. Tecuci by the indicated deadline (making sure that the files are not too large).


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.