Catalog Data: 4720. Introduction to Artificial Intelligence. (3). (Same as Comp 4720). Fundamentals of programming in LISP. Central ideas of artificial intelligence, including heuristic search, problem solving, slot-and-filler structures, and knowledge representation. PREREQUISITE: Permission of Instructor or EECE 3221

1. Previous and recent programming experience in at least one high-level language.
2. Familiarity with elementary data structures and algorithms.
3. Mathematical maturity consistent with senior standing in Electrical Engineering, Computer Engineering, or Computer Science.

Textbook: Artificial Intelligence: A Modern Approach, Stuart Russell and Peter Norvig, Prentice Hall, 1995.

Coordinator: David J. Russomanno, Associate Professor of Electrical Engineering and Computer Engineering

Course Objectives: This course is designed to introduce seniors in Electrical Engineering, Computer Engineering, and Computer Science to the classical topics of Artificial Intelligence in the context of intelligent agent design while providing experience in implementing algorithms in a high-level computer language.

Relationship to Program Educational Objectives: The Artificial Intelligence (AI) course supports Computer Engineering objectives one and two by emphasizing fundamental principles of intelligent systems by covering the underlying mathematics as well as the implementation of AI algorithms using a high-level programming language.

An ability to apply knowledge of mathematics, science and engineering (a)

An ability to identify, formulate and solve engineering problems (e)

An ability to communicate effectively (g)

Students’ learning is assessed by graded assignments (10%), pop quizzes (15%), two exams (40%), a final exam (20%), and a design project (15%). Students also assess the instructor and the course by completing an SIRS questionnaire at the end of the term.

1. Introduction to Artificial Intelligence (AI) History, Foundations, and State of the Art (1.5 hours)
2. Introduction to Intelligent Agent Structure and Enviornments (1.5 hours)
3. Uniformed Search: Formulating Problems, Breadth First, Uniform Cost, Depth First, Iterative Deeping (1.5 hours)
4. Constraint Satisfaction (1.5 hours)
5. Informed Search: Hill Climbing, Simulated Annealing, Best-First, Dynamic Programming, A* (4.5 hours)
6. Game-Playing (4.5 hours)
7. Introduction to Logic-Based Agents (3 hours)
8. First-Order Logic (3 hours)
9. Inference in First-Order Logic (6 hours)
10. Logical Reasoning Systems (6 hours)
11. Knowledge Representation and Inference for Intelligent Agent Design (6 hours)
12. In-Class Assessment: Examinations, Pop Quizzes, and Final Exam (6 hours)

One term programming project is assigned during the course. The student can choose from UNIX, VMS or Windows operating system platforms and can use C/C++, Java, Prolog, or LISP for a high-level language for implementing the term project.

Design: The programming project requires the student to use top-down development consisting of analysis, design, implementation, test, and evaluation stages.

Contribution to Professional Component:

Engineering Science: 2 credits or 67%

Engineering Design: 1 credit or 33%

Communication: Students must communicate their knowledge of the final design project in a formal written report.

Prepared By: D. J. Russomanno Date: August 23, 2002