Table of Contents

T-622-ARTI, Introduction to Artificial Intelligence, Spring 2009

Basic Info

Description

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.

Goals

On the completion of the course the students should:

Book

The textbook for this class is: “Artificial Intelligence: A Modern Approach (Second 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.

AssignmentCodeDescriptionMaterialAssignedDueWeight
Program 1PROG1First Programming Assignment Ch. 1-3 Jan 26 Feb 9 5%
Problems 1PROB1First Problem Set Ch. 4-5 Feb 9 Feb 16 5%
ProposalFP-PROPSubmission of Final Project Proposal - - Feb 24 0%
Program 2PROG2Second Programming Assignment Ch. 4-6 Feb 16 Mar 2 5%
Problems 2PROB2Second Problem Set Ch. 7-8 Mar 6 Mar 16 5%
Final ProjectFPFinal Programming Project with Demo All - Mar 31 / Apr 3 30%
Total 50%

Paper Discussion (20%)

After every Tuesday 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 Friday 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 Friday 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 Tuesday class, chosen questions from those submitted will be discussed by the group as a whole and you are expected to participate.

DueThreadReadingComments
Jan 19 Thread 1 "Toward a Critical Technical Practice: Lessons Learned in Trying to Reform AI" You only need to read sections 2, 3 and 4
Jan 23 Thread 2 "Computing Machinery and Intelligence" You may read a summary if you prefer
Jan 30 Thread 3 "Programming Intelligence: The Piecemeal Approach" An overview article. Relatively easy.
Feb 6 We will continue with the discussion from the previous week
Feb 13 Thread 4 "Simulation-Based Approach to General Game Playing" Guest: Yngvi Björnsson
Feb 20 Thread 5 "The Open Mind Common Sense Project"
Feb 27 Connect 4 Tournament!
Mar 6 Thread 6 "Activity Planning for The Mars Exploration Rovers" Guest: Ari K. Jónsson
Mar 13 Thread 7 "The DARWARS Tactical Language Training System" “Guest”: Hannes
Mar 20 Thread 8 "A Mind Model for Multimodal Communicative Creatures and Humanoids" Guest: Kristinn Thorisson

Course Schedule

WeekDateChaptersTopicAssignedDue
1Jan 13 1Introduction+History
Jan 16 2Intelligent Agents
2Jan 19 LabLisp (Lab material) Q
Jan 20 3Search Problems
Jan 23 3Blind Search Q
3Jan 26 LabAgents (lab material) PROG1
Jan 27 4Heuristic Search A
Jan 30 4Heuristic Search B Q
4Feb 02 LabAgents and A* (lab material)
Feb 03 5Constraint Satisfaction A
Feb 06 5Constraint Satisfaction B Q
5Feb 09 LabFormulating search problems (lab material)PROB1PROG1
Feb 10 6Adversarial Search
Feb 13 6Adversarial Search (same slides) Q
6Feb 16 LabReview of PROG1 PROG2PROB1
Feb 17 7Guest: Yngvi
Feb 20 7Propositional Logic Q
7Feb 23 LabReview of PROB1
Feb 24 8First-Order Logic FP-PROP
Feb 27 8First-Order Logic / PowerLoom Q
8Mar 02 Lab PROG2
Mar 03 Connect 4 Tournament
Mar 06 11PlanningPROB2Q
9Mar 09 Lab
Mar 10 11Guest: Ari
Mar 13 13,14Uncertainty / Bayesian nets Q
10Mar 16 LabBayesian nets (lab material) PROB2
Mar 17 18-21“Guest”: Hannes
Mar 20 18-21Learning Q
11Mar 23 Lab Review of PROB2
Mar 24 22-25Guest: Kristinn
Mar 27 22-25Embodied Conversational Agents: REA
12Mar 30 LabExam Review
Mar 31 FP
Apr 03 FP

Grading

Part of CourseTotal Weight
Discussion 20%
Programming Assignments (x2) 10%
Problem Sets (x2) 10%
Final Project 30%
Final Written Exam 30%
Total 100%