Emre Ugur

Ph.D.

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CMPE540 Principles of Artificial Intelligence
Tuesday 14:00-17:00, BM A3

Aim: General problem solving methods in artificial intelligence. Search methods. Production systems. Games and heuristics. Knowledge representation. Artificial Intelligence Languages.
Text Book: Russell and Norvig, Artificial Intelligence: A Modern Approach, 3rd ed.
Lecture slides: Available at the course page.
Instructor: Emre Ugur (contact)
Office hours: Tuesday, 17:00-18:00
Mailing-list: Please send email if you are not registered!
Grades

Schedule (subject to change):

Sep 20	Agents & Uninformed search	Part1, Part2
Sep 27	A* search, heuristics; local search; search-based agents	Slides
Sep 30	Project 1 is out. Due: Oct 16 midnight	Link
Oct 1	Game playing, constraint satisfaction problems	Slides
Oct 4	No class
Oct 11	Midterm 1
Oct 18	Propositional logic: semantics and inference; logical agents	Slides
Oct 25	First-order logic (FOL)	Slides
Nov 1	Project 2 is out! Due: Nov 20 midnight	Link
Nov 1	Inference in first-order logic	Slides
Nov 8	Probability, Bayes nets, inference	Slides
Nov 15	Midterm 2
Nov 22	Project 3 is out. Due: Dec 11 midnight	Link
Nov 22	Review of Bayes nets, intro to temporal models	Slides
Nov 29	Markov Models, Hidden Markov Models	Slides
Dec 6	Inference in Markov Models, intro to Machine Learning	Slides
Dec 9	Project 4 is out. Due: Dec 23 midnight	Link
Dec 13	Advanced Topics: Robotics and Deep Learning
Dec 30	Final Exam	Location: TBD

Grading:

• Quizzes: 15%
• Midterms: 25%
• Final: 25%
• Projects: 35%

Projects: 3 or 4 programming projects. C/C++ will be used as the programming language and Linux will be used as the environment. (-10% x day) penalty for late submissions upto 3 days.
Quizzes: One quiz in each lecture at a random time. Please bring your own paper.
Cheating: Any sharing or copying will be considered as cheating. Please do not cheat! See CMPE procedures for cheating behavior.