CS 461 Artificial Intelligence
Spring 2014
Instructor: 
Aynur Dayanık 
Office: 
Engineering Building, EA426 
Phone: 
x3441 
Email: 

Lectures: 
Tuesday 9:3010:20 and Thursday 10:3012:20 at EB102 
Office Hours: 
TBA 
TA: 
Anıl Armağan 
Course Description:
This course provides an introduction to artificial intelligence. We will start with problemsolving techniques, blind search algorithms (breadthfirst, depthfirst, iterative deepening, and other strategies), heuristic search algorithms (A*), and gameplaying. And then we will discuss constraint satisfaction problems. We will cover knowledge representation and reasoning: syntax, semantics, and proof theory of propositional logic and firstorder predicate logic, uncertainty and probabilistic reasoning. We will also discuss machine learning and natural language processing.
Moodle page of the course:
Check regularly the Moodle page of the course for lecture notes, homework assignments, and announcements.
Textbook:
Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (AIMA), PrenticeHall (2010), 3rd Edition..
Course Outline:
Introduction
Intelligent Agents
Solving problems by searching
Informed search and exploration
Adversarial search
Constraint Satisfaction Problems
Logical agents
Firstorder logic
Inference in firstorder logic
Knowledge representation
Uncertainty
Probabilistic reasoning
Learning from observations
Statistical learning methods
Natural language processing
Course requirements:
There will be three inclass quizzes (15%) with advance notice, two homework assignments (10%) involving programming and discussion, one midterm exam (40%) and one final exam (35%).
In order to be able to take the final exam, one must obtain at least 22 points (40% of total 55) from the weighted sum of the quiz and midterm grades; else one will receive FZ.
Check regularly the Moodle page of the course for lecture notes, homework assignments, and announcements.