Announcements:

syllabus available below: follow the links

the take-home final is now available: here, due on Sunday May, 7 @11:59pm

Description of the class

Syllabus of Spring 05 available here (no major changes to be expected)

The objective of this course is to provide the students with a general understanding of artificial intelligence:

what is artificial intelligence? this is now a familiar term, but what is this about after all?

what are the main research areas in artificial intelligence? what people, working in making computers "intelligent", are interested in?
      * make a robot able to find its path to a goal?
      * enable a computer to deduce information from knowledge? even when knowledge is
      partial, and / or uncertain
      * design machines able to learn?
      * enable robot to "see"? "hear"? "speak" properly?
      * how robots / agents interact together?
In particular, in class, we will review the above-mentioned topics, describe the corresponding techniques, learn how to recognize what kind of problem we tackle, etc.
As many practical problems (i.e., from real-life) as possible will be presented in class.

Students will also have to work on a project. Teams will be defined, and each team will have to pick up a subject for their project among a list of AI-related topics. They will team-work on this project all semester long, and will have to submit a report (+ program code) of their work at the end of the semester.

As far as assignments and exams , there will be:

reading assignments, and homework assignments (randomly checked); additional assignments for grad students;

(announced AND un-announced) quizzes throughout the semester;

1 semester-long in-team project;

1 mid-term;

1 final exam.

More details about the class: a tentative schedule

This class will meet every Mondays, and Wednesdays, from 1:30 to 2:50pm, in room 322. The textbook for this class is: "Artificial Intelligence: A Modern Approach" (2nd Edition), by Stuart J. Russell, Peter Norvig. Check the progress of the class:

week #1: Presentation of the syllabus (only one class)

week #2: Introduction to AI; quizz to determine the projects

week #3: Agents: definition, use, properties

week #4: Knowledge representation

week #5: Propositional logic

week #6: Predicate logic

week #7: Expert systems

week #8: Reasoning under uncertainty

week #9: SPRING BREAK; take-home mid-term (due March 22)

week #10: Problem solving

week #11: Problem solving

week #12: Problem solving

week #13: Game-Playing: alpha-beta pruning and minimax

week #14: Game Playing: alpha-beta pruning and imperfect real-time decision methods

week #15: Session on projects / Game Playing

week #16: Constraint solving / Review

week #17: week of the final exam

Material for the class:

"ToDo" list:

During Spring Break: 2nd deliverable of your AI project (due on March 25); take-home mid-term (due on March 22)

Exercises given in class:

General intro to AI: here

Logic and First-order logic: 1, 2

Exercises on First-Order Logic, including solutions: here

Problem-solving: here

References, and other material:

Lecture notes of the first class: an introduction to AI (here)

Lecture notes about: agents (here)

Lecture notes about: knowledge representation (here)

Lecture notes about: expert systems (here)

Lecture notes about: reasoning under uncertainty (probabilities) (here)

Quizzes and Exams:

quiz 0 (to determine project teams); quiz 1; quiz 2; quiz 3; quiz 4

midterm: available here, take-home due by March 22, no lateness allowed.

final: available here, take-home due by May 7, no lateness allowed.

Projects:

Description of projects:

here, for an archive containing all projects except for the engineering one (about robotics + 3-D. animation)

or consult each project at a time: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10

In this section, you can access the list of teams, along with the description of the project and advise:

Team 1 -- Text analysis: members, description of project, advise 1, tutorial

Team 2 -- Ask Anna: members, description of project, advise 1, tutorial

Team 3 -- Automated management of inconsistent problems: members, description of project, advise 1, tutorial, tutorial

Team 4 -- AI and Engineering: members, description of project, advise 1, tutorial

Team 5 -- Reliable computations for high assurance systems: members, description of project, advise 1, tutorial

Team 6 -- Sudoku helper: members, description of project, advise 1, tutorial

Team 7 -- Job scheduler: members, description of project, advise 1, tutorial

Team 8 -- Game playing/Othello: members, description of project, advise 1, tutorial

Team 9 -- Game playing/Othello: members, description of project, advise 1, tutorial

Martine Ceberio

Last modified: Mon Sep 4 22:45:15 MDT 2006