DTAD20: Advanced Artificial Intelligence

Instructor: Keith Downing (keithd@idi.ntnu.no)

Office at Ostersund: Q383

Office at NTNU: Room 308 IT-Vest (73590271)

First lecture : Jan. 18, 2005

Official Lecture/Lab Time & Room Schedule

Course Syllabus (Lectures, Labs, Assignments)


Course Overview

This class covers several advanced artificial-intelligence (AI) techniques, mainly of the symbolic type. The primary topics are uncertainty reasoning and machine learning, while robotics, machine perception, and AI philosphy and ethics may receive brief coverage.

This course emphasizes hands-on experience with the above AI techniques, so students will work with computer programs that perform these tasks and will, in most cases, write these programs themselves. For student-written programs, the language can be any of the following: Prolog, Lisp, C, C++, JAVA, unless otherwise specified by the instructor.


Artificial Intelligence: A Modern Approach

Chapters (tentative): 13-21, 24,25,26,27

Lecture Notes

Homework Options

UC Irvine Machine Learning Repository (Lotsa data sets!)

Fathom Resource Center (more data sets)

A few special data sets for this course

Grading Policy

The final grade will be entirely based on the demonstrated results of the 4 projects plus any other homework exercises. There is no final exam.

Labs can be worked on in groups of no more than 2 members.