Bruce R. Maxim, PhD
Associate Professor
Office: 120 ELB
Phone: 436-9155
Office Hours: 12:30 M & 3:30 TTh
e-mail: bmaxim@umich.edu
 

This course is intended to provide an overview of the problems and methods studied in the field of artificial intelligence. The focus of the course will be on the study of methods of knowledge representation, data structures, and algorithms useful to the development of intelligent programs. The course will also include discussion of important applications of AI methodology.

Your scores on the projects and exams will determine your grade in this course. There will be three exams, including a final exam, an oral presentation, and 4 lab projects using several AI tools (including LISP), not all of which will require the development of complete programs from scratch. The exams will count for 50% of your grade, the oral presentation 10%, and the projects 40%. Late work will be penalized, as will evidence of cheating in any form.
 

Texts: Artificial Intelligence (3rd Edition) by G. Luger and
       W. Stubblefield, Addison-Wesley, 1997. (Required)

       Lisp (3rd Edition) by P. Winston and B. Horn, Addison-
       Wesley, 1989. (Required)

URL: www.engin.umd.umich.edu/CIS/course.des/cis479.html
 
 

Date	Topic	Reading
05-08	Lisp: Primitives, Predicates, and Conditionals	L1,W1-W4
05-10	Lisp: Iteration, I/O, Recursion, Data Structures, and Macros	W5-W12,W17
05-15	Intelligent Search	L3,W19
05-17	Game Playing Project 1 due	L4
05-22	Production Systems and Matching Expert Systems	L5,W24 L6,W25-W27
05-24	Exam 1 Uncertainty	L7
05-29	Probabilistic Reasoning Project 2 due	L7
05-31	Knowledge Engineering Tools Predicate Logic	Notes L2,L9
06-05	Knowledge Representation	L8
06-07	Planning Intelligent Agents and SOAR Project 3 due	L12 L16
06-12	Exam 2 Machine Learning	L13
06-14	Neural Networks Genetic Algorithms	L14 L15
06-19	Natural Language Understanding Object-Oriented AI Project 4 due	L11 L10
06-21	Oral Presentations (3:00 - 7:00 pm)
06-28	Final Exam (3:30-6:30)