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T-622-ARTI, Introduction to Artificial Intelligence, Spring 2011

Basic Info

  • Instructor: Hannes Högni Vilhjálmsson (, on MSN)
  • Assistant: Angelo Cafaro (
  • Office: 2nd floor, Venus, 559-6323, 824-8814
  • Theory Lectures: Mondays 13:10-14:45, Fridays 10:20-11:55 (M.1.02)
  • Paper Discussion: Mondays 13:10-14:45 (M.1.02)
  • Labs: Thursdays 14:00-15:40 (M.1.03)
  • Online Forum: (You need to register using your own name)


Artificial intelligence (AI) is devoted to the computational study of intelligent behavior, including areas such as problem solving, knowledge representation, reasoning, planning and scheduling, machine learning, perception and communication. This course gives an overview of the aforementioned AI subfields from a computer science perspective and introduces fundamental solution techniques for addressing them. An important part of the course is an independent final project where the students develop AI software in an area of their choice.


On the completion of the course the students should:

  • have a good overview of the field of artificial intelligence (AI) and a thorough understanding of the fundamental solution methods used to attack a wide variety of AI-related problems.
  • have gained experience building a small special-purpose AI system.


The textbook for this class is: “Artificial Intelligence: A Modern Approach (Third Edition)” by Stuart Russell and Peter Norvig. This book has a very good web site full of useful AI resources.

Coursework Overview

Assignments (50%)

You complete two programming assignments, two problem sets and a final programming project. These can all be group projects (up to 3 people). Make sure you clearly indicate who is part of the group. Remember that the assignments and problem sets is practice for the final exam, so all group members should make sure they understand the solution. You should discuss final project ideas with instructor in week 6, hand in a proposal in week 7 and demonstrate final project in week 12. Everything that has to be turned in, should arrive no later than at 23:59 on the due date, or else incur 10% penalty for each additional day, including weekends and holidays.

Program 1PROG1First Programming Assignment Ch. 1-3 Jan 27 Feb 10 5%
Problems 1PROB1First Problem Set Ch. 4-5 Feb 10 Feb 17 5%
Final Project ProposalFP-PROPSubmission of Final Project Proposal - - Feb 24 0%
Program 2PROG2Second Programming Assignment Ch. 4-6 Feb 17 Mar 3 5%
Problems 2PROB2Second Problem Set Ch. 7-8 Mar 4 Mar 17 5%
Final ProjectFPFinal Programming Project with Demo All - Mar 28-31 30%
Total 50%

Paper Discussion (20%)

After every Monday class, the instructor will post a link on the course online forum to a paper or article on an interesting aspect of Artificial Intelligence. This may or may not be directly related to the book chapter being covered that week.

You need to read this paper or article by the end of Sunday and post, under the same forum thread, 2 questions you have about the contents of the reading. This post has to arrive by 23:59 on Sunday night to count towards your paper discussion grade. The questions can point out concepts that you have difficulty understanding, but preferably they should be questions that provoke discussion from the material. No grade will be given for these questions, you automatically get points for being on time.

In the discussion section of the following Monday class, chosen questions from those submitted will be discussed by the group as a whole and you are expected to participate.

Jan 17 "Toward a Critical Technical Practice: Lessons Learned in Trying to Reform AI" You only need to read sections 2, 3 and 4
Jan 24 "Computing Machinery and Intelligence" You may read a summary if you prefer
Jan 31 "Programming Intelligence: The Piecemeal Approach" An overview article. Relatively easy.
Feb 07 When Gravity Fails: Local Search Topology (quite heavy, but give it a try) Guest: J. Deon Garrett (from IIIM)
Feb 14 "CADIA PLAYER: A Simulation-Based General Game Player" Guest: Yngvi Björnsson
Feb 21 "The Open Mind Common Sense Project"
Feb 28 "Spontaneous Avatar Behavior for Human Territoriality" Guest: Claudio Pedica (from IIIM)
Mar 07 "Activity Planning for The Mars Exploration Rovers" Guest: Ari K. Jónsson
Mar 14 "From Constructionist to Constructivist A.I." Guest: Kristinn R. Thórisson
Mar 21 "The DARWARS Tactical Language Training System “Guest:” Hannes

Course Schedule

1Jan 10 1Introduction+History
Jan 13 LabLisp (Lab material) (Introduction to Lisp)
Jan 14 2Intelligent Agents
2Jan 17 3Search Problems (updated!) Q
Jan 20 LabAgents (lab material)
Jan 21 3Search Problems (continued)
3Jan 24 3Blind Search Q
Jan 27 LabBraitenberg Vehicles (lab material) (Braitenberg Vehicles)PROG1
Jan 28 3Heuristic Search A
4Jan 31 3Heuristic Search B Q
Feb 03 LabA* Pathfinding Search (lab material)
Feb 04 5Adversarial Search
5Feb 07 5Guest: Deon Garrett Q
Feb 10 LabFormulating Search Problems (lab material)PROB1PROG1
Feb 11 5Adversarial Search (continued)
6Feb 14 7Guest: Yngvi Björnsson Q
Feb 17 LabReview of PROG1 PROG2PROB1
Feb 18 7Propositional Logic
7Feb 21 8Common Sense Discussion Q
Feb 24 LabReview of PROB1 FP-PROP
Feb 25 8First-Order Logic
8Feb 28 Guest: Claudio Pedica Q
Mar 03 LabPowerLoom (lab material) PROG2
Mar 04 10PlanningPROB2
9Mar 07 10Guest: Ari Jónsson Q
Mar 10 Lab Connect 4 Tournament
Mar 11 13,14Uncertainty / Bayesian nets
10Mar 14 NAGuest: Kristinn R. Thórisson Q
Mar 17 LabBayesian Nets (lab material) PROB2
Mar 18 18-21Learning
11Mar 21 NA“Guest:” Hannes Q
Mar 24 LabBayesian Nets Excercise + Review of PROB2
Mar 25 Exam Review
12Mar 28 Other AI Resources and Discussions
Mar 31 Final Project Demos / Presentations FP
Apr 01 Final Project Demos / Presentations FP


Part of CourseTotal Weight
Discussion/Participation 20%
Programming Assignments (x2) 10%
Problem Sets (x2) 10%
Final Project 30%
Final Written Exam 30%
Total 100%
/var/www/ · Last modified: 2011/03/29 23:19 by hannes

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