Course Overview

LecturesTue. & Thu. 12:00 - 1:20pm in Wean Hall 5403
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This course is about the theory and practice of Artificial Intelligence. We will study modern techniques for computers to represent task-relevant information and make intelligent (i.e. satisficing or optimal) decisions towards the achievement of goals. The search and problem solving methods are applicable throughout a large range of industrial, civil, medical, financial, robotic, and information systems. We will investigate questions about AI systems such as: how to represent knowledge, how to effectively generate appropriate sequences of actions and how to search among alternatives to find optimal or near-optimal solutions. We will also explore how to deal with uncertainty in the world, how to learn from experience, and how to learn decision rules from data. We expect that by the end of the course students will have a thorough understanding of the algorithmic foundations of AI, how probability and AI are closely interrelated, and how automated agents learn. We also expect students to acquire a strong appreciation of the big-picture aspects of developing fully autonomous intelligent agents. Other lectures will introduce additional aspects of AI, including natural language processing, web-based search engines, industrial applications, autonomous robotics, and economic/game-theoretic decision making.


Ziv Bar-JosephZiv Bar-Joseph
Office Wean Hall 4107
eMail, URL zivbj at cs,
Office Hours Tue. 1:30 - 3:00pm
Illah NourbakhshIllah Nourbakhsh
Office Newell-Simon Hall 3115
eMail, URL illah at cs,
Office Hours Thu. 10:30 - 12:00pm


Hetunandan KamichettyHetunandan Kamichetty
OfficeDoherty Hall 4302C (directions)
eMail, URL hetu at cs,
Office Hours Wed. 4:30 - 6:00pm
Henry LinHenry Lin
Office Newell-Simon Hall 4505
eMail, URL thlin at cs,
Office Hours Mon. 3:00 - 4:30pm

Administrative Assistant

Michelle Martinmichelle324 at cs, Wean Hall 4619

Course Structure

The requirements of this course will consist of participating in lectures, five problem sets, midterm and final. The grading breakdown is as follows:

For most of the class we will follow the book:

  • Artificial Intelligence: A Modern Approach 2nd Edition. by Russell and Norvig (Prentice Hall).
  • Problem Sets

    We will have five problem sets. Problem sets will consist of both theoretical and programming assignments. On some assignments we will recommend that students program in Matlab. However, you are free to do your assignments in any programming language you like as long as you clear it with the TAs first. We will hold a Matlab tutorial during the first week of classes for those who are not familiar with this language.

    While you are permitted to discuss the problem sets with fellow class members, each student must write the solutions and code on her / his own. Problem sets are due at the beginning of class on their due date.

    Late Homework Policy

    In any case of personal problems preventing you from submitting your answers on time, please contact the instructors or TAs as soon as possible (before the problem set is due). If you do not have a good enough reason for a late submission you will be penalized according to the following policy:

    You must turn in all of the homeworks, even if for zero credit, in order to pass the course. Turn in all late homework assignments to Michelle Martin.

    Midterm and Final

    The midterm will take place during class hours (see schedule). The date and room of the final exam will also be announced later. We will be holding review sessions prior to the midterm and the final. More information will be provided later in the class.