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:
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.
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.
Assignment | Code | Description | Material | Assigned | Due | Weight |
---|---|---|---|---|---|---|
Program 1 | PROG1 | First Programming Assignment | Ch. 1-3 | Jan 26 | Feb 9 | 5% |
Problems 1 | PROB1 | First Problem Set | Ch. 4-5 | Feb 9 | Feb 16 | 5% |
Proposal | FP-PROP | Submission of Final Project Proposal | - | - | Feb 24 | 0% |
Program 2 | PROG2 | Second Programming Assignment | Ch. 4-6 | Feb 16 | Mar 2 | 5% |
Problems 2 | PROB2 | Second Problem Set | Ch. 7-8 | Mar 6 | Mar 16 | 5% |
Final Project | FP | Final Programming Project with Demo | All | - | Mar 31 / Apr 3 | 30% |
Total 50% |
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.
Due | Thread | Reading | Comments |
---|---|---|---|
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 |
Week | Date | Chapters | Topic | Assigned | Due |
---|---|---|---|---|---|
1 | Jan 13 | 1 | Introduction+History | ||
Jan 16 | 2 | Intelligent Agents | |||
2 | Jan 19 | Lab | Lisp (Lab material) | Q | |
Jan 20 | 3 | Search Problems | |||
Jan 23 | 3 | Blind Search | Q | ||
3 | Jan 26 | Lab | Agents (lab material) | PROG1 | |
Jan 27 | 4 | Heuristic Search A | |||
Jan 30 | 4 | Heuristic Search B | Q | ||
4 | Feb 02 | Lab | Agents and A* (lab material) | ||
Feb 03 | 5 | Constraint Satisfaction A | |||
Feb 06 | 5 | Constraint Satisfaction B | Q | ||
5 | Feb 09 | Lab | Formulating search problems (lab material) | PROB1 | PROG1 |
Feb 10 | 6 | Adversarial Search | |||
Feb 13 | 6 | Adversarial Search (same slides) | Q | ||
6 | Feb 16 | Lab | Review of PROG1 | PROG2 | PROB1 |
Feb 17 | 7 | Guest: Yngvi | |||
Feb 20 | 7 | Propositional Logic | Q | ||
7 | Feb 23 | Lab | Review of PROB1 | ||
Feb 24 | 8 | First-Order Logic | FP-PROP | ||
Feb 27 | 8 | First-Order Logic / PowerLoom | Q | ||
8 | Mar 02 | Lab | PROG2 | ||
Mar 03 | Connect 4 Tournament | ||||
Mar 06 | 11 | Planning | PROB2 | Q | |
9 | Mar 09 | Lab | |||
Mar 10 | 11 | Guest: Ari | |||
Mar 13 | 13,14 | Uncertainty / Bayesian nets | Q | ||
10 | Mar 16 | Lab | Bayesian nets (lab material) | PROB2 | |
Mar 17 | 18-21 | “Guest”: Hannes | |||
Mar 20 | 18-21 | Learning | Q | ||
11 | Mar 23 | Lab | Review of PROB2 | ||
Mar 24 | 22-25 | Guest: Kristinn | |||
Mar 27 | 22-25 | Embodied Conversational Agents: REA | |||
12 | Mar 30 | Lab | Exam Review | ||
Mar 31 | FP | ||||
Apr 03 | FP | ||||
Part of Course | Total Weight |
---|---|
Discussion | 20% |
Programming Assignments (x2) | 10% |
Problem Sets (x2) | 10% |
Final Project | 30% |
Final Written Exam | 30% |
Total 100% |