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Instructor: Pinar Duygulu
Office : EA 433
e-mail : duygulu[at]cs.bilkent.edu.tr
Phone : (312)
290 31 43
Office hours: by appointment..
Teaching
Assistant:
Course web page: http://www.cs.bilkent.edu.tr/~duygulu/Courses/CS461/index.html
Textbook:
Artificial Intelligence:A Modern Approach
(AIMA), Stuart Russell & Peter Norvig,
Prentice-Hall (2003), 2nd Edition
Time & Location: Mondays :
9:00-10:30, Wednesdays 10:40-12:30
EB203
Course Description:
What is artificial intelligence? Problem-solving techniques: state-space
approach, problem-reduction approach, problem model, problem representation,
exhaustive search algorithms (breadth-first, depth-first, iterative deepening,
and other strategies), heuristic search algorithms (A*). Game-playing. Knowledge representation and reasoning: syntax,
semantics, and proof theory (deductive inference) of propositional logic,
first-order predicate logic, production systems, semantic nets, and frames.
Knowledge base, expert systems, inference engine.
Machine learning: inductive inference, analogical inference, abductive inference, learning by instruction, learning from
examples, conceptual clustering, explanation-based learning, connectionist
learning (neural networks). Vision, robotics
Topics:
Introduction
Intelligent
agents
Solving problems by searching
Informed search and
exploration
Adversarial search
Logical agents
First-order
logic
Inference in first-order logic
Knowledge
representation
Uncertainty
Probabilistic reasoning
Learning from
observations
Statistical learning
methods
Perception/Vision
Robotics
Philosophical
Foundations
Grading:
Homeworks (30%)
Quizzes
(25%)
Midterm (25%)
Final
(25%).
Participation (upto 5%)
•Midterm
and final are closed book exams.
For quizzes you can use book and notes.
•Participation does not mean attendance, you may get
positive points by actively participating to the discussion, by answering the
questions during the class or get negative points if you distract the
lectures
Related Links
About AI (an amazingly
good web site maintained by AAAI)
How
to do research at the MIT AI Lab
HAL's Legacy
Selmer Bringsjord's "The Intro to AI Show"
An excellent demo of various
search strategies (useful when studying Chs. 3 & 4
of AIMA)
Other
useful AI demos, projects, etc.
Advice
Homework must be written
using a document processing system. No handwritten stuff!
If it is a
programming homework attach all the code YOU have written and give pointers to
the code you have REUSED (with slight modifications).
Material should be
submitted on the due date to the TA (and NOT to the instructor).
Late
submissions are not accepted.
Cheating, plagiarism, etc. will be severely
punished and disciplinary action will be taken.
Announcements:
Midterm:
Assignments:
Lectures
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Wumpus
World
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Knowledge
Representation |
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Uncertainty
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Bayesian
Networks |
Chapter 14 from AIMA
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Chapter from AIMA
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