CMSC 671: Introduction to Artificial Intelligence
Fall 2010
Course Information
Instructor and Office Hours
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Instructor: Laura Zavala
Email: laura.zavala @ umbc.edu
Office: ITE 373
Office Phone: 410-455-8775
Mobile: 803-447-6298
Office Hours: Mondays and Wednesdays 1:30-2:30
Class Time and Location
Tuesday and Thursday 2:15 - 3:30 PM
UMBC Research Park, RMF Engineering Building, 1st floor Conference Room
5520 Research Park Drive
Course Description
This course provides an introduction to artificial intelligence concepts and techniques. Specific topics we will cover include the agent paradigm in AI systems, search, game playing, knowledge representation and reasoning, logical reasoning, planning, uncertain reasoning and Bayes nets, multi-agent systems, machine learning, the history and philosophy of AI, and the Lisp programming language.
Prerequisite
The equivalent of an undergraduate degree in computer science. In particular, students should have completed CMSC 341 (or the equivalent) and have strong programming skills. CMSC 441 or exposure to the theory of complexity of algorithms will also be useful. You should know the fundamentals of propositional and first-order logic, probability theory, and big-O complexity analysis. A pretest will be given to assess your familiarity with this material.
Textbook
Honor Code
By enrolling in this course, each student assumes the responsibilities of an active participant in UMBC's scholarly community in which everyone's academic work and behavior are held to the highest standards of honesty. Cheating, fabrication, plagiarism, and helping others to commit these acts are all forms of academic dishonesty, and they are wrong. Academic misconduct could result in disciplinary action that may include, but is not limited to, suspension or dismissal. To read the full Student Academic Conduct Policy, consult the UMBC Student Handbook, the Faculty Handbook, or the UMBC Policies section of the UMBC Directory.
Acknowledgements
Thanks to Dr. Marie desJardins for making her course materials available. Many of the course materials for this class have been adapted from Dr. desJardins' course.