About
Basic concepts of artificial intelligence. Topics include: defining the problem as a state space search, production systems; heuristic search; basic problem-solving methods; game playing; knowledge representation using predicate logic, semantic nets, frames, and scripts; non-monotonic reasoning, statistical and probabilistic reasoning.
Course Information
Introduction to Artificial Intelligence
ITCS 3153
The University of North Carolina at Charlotte
Department of Computer Science
Rotation: every Spring term
Next/Current Course Offering:
Spring 2012
Undergraduate #21940 ITCS 3153-001
9:30a – 10:45a TR
135 Woodward Hall
Jan 09, 2012 – May 01, 2012
Final Exam: Thursday, May 10, 8:00a – 10:30a
Professor: G. Michael Youngblood, Ph.D.
Office Hours: 11:00a-NOON TR or by appointment
Office: 435A Woodward Hall
Phone: 704.687.7989
TA/Grader: Eric Faust
Office Hours: 11a-NOON W, 1p-2p F, or by appointment (email)
Office: 453 Woodward (Games + Learning Lab)
Phone: 704.687.7445
Historical Course Offering:
None before this matter.
Prerequisites:
ITCS 3152 Symbolic Programming
Ability to Program using a High-Level Computer Language
Knowledge and Application of Algorithms (and Data Structures Recommended)
ITCS 2214 Data Structures
ITCS 2215 Design and Analysis of Algorithms Recommended
ITCS 1213 and 1213L with a grade of C or better
ITCS 1212 and 1212L with a grade of C or better
Discrete Math Course Recommended
MATH 1100 or MATH 1103 or MATH 1120 or MATH 1241
Required Textbooks:
1. Artificial Intelligence: A Modern Approach, 3/e
Stuart Russell, Peter Norvig
Book website
2. Javascript: The Definitive Guide
David Flanagan.
