Instructor: Prof. Harry Wechsler email@example.com
Course Description – Principles and methods for knowledge representation, reasoning, problem solving, planning, heuristic search, reasoning, learning, probabilistic reasoning, and natural language processing and their application to building intelligent systems in a variety of domains. LISP, PROLOG, MATLAB, or
expert system programming language.
Prereq: CS 310 and CS 330
Main Topics: Problem Solving, Search, Knowledge Representation and Reasoning, Uncertainty and Probabilistic Reasoning, Machine Learning, Connectionism and Neural Networks, and Natural Language Processing. Additional topics time permitting: Deep Learning and Biometrics.
Time, Day, and Venue: W – Wednesday, 4:30 pm - 7:10 pm
Innovation Hall 208
Office Hours: W 3:15 – 4:15 pm or by appointment, ENGR 4448.
First day of classes: W, January 25, 2017
Spring break: week of March 13
Last day of classes: W, May 3
FINAL Exam: W, May 10, 4:30 – 7:15 pm
Textbook: Artificial Intelligence: A Modern Approach, Russell and Norvig (3rd ed.), Prentice Hall, 2010.
Textbook Website: http://aima.cs.berkeley.edu/
Textbook Slides: http://aima.eecs.berkeley.edu/slides-pdf/
CLOSED BOOK EXAMINATIONS
· Homework – 15 % // late homework not accepted //
· GAME TEAM assignment DUE March 20, 2017 – 10 %
· CHOICE AI TEAM assignment DUE April 26, 2017 – 15 %
· Midterm – W, March 22, 2017 – 20 %
· (Cumulative) Final – May 10, 2017 – 40 %
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