Overview

We meet MW from 8:10 am – 9:25 am in FGH 258.

My assumption is that you’ve had an good introductory course in AI. CS 4260 or CS 5260, or an equivalent, is the prerequisite for this course.

The textbook for the course is Third Edition of Russell and Norvig’s “Artificial Intelligence: A Modern Approach“. We will be reading from this text, as well as research papers each week.

Readings: Each week for the first part of the semester I expect that we’ll be reading from the textbook and 1-2 papers on a topic that roughly follows the table of contents of the text, but these readings will go beyond the topics addressed in depth in the text. The coverage will include topics that are covered by other AI faculty so that there is some common “core” of material across the CS 6360 offerings. The prior and current themes include (1) Search algorithms for problem solving; (2) Planning and scheduling algorithms; (3) Reasoning and Decision Making with Uncertain Knowledge; and (4) Machine Learning.

However, I will add some additional topics, and you will nominate some of the required readings.

Each Monday we will discuss the readings. On Wednesdays we will continue the discussion, but I’ll also ask you to summarize one or more papers related to the Monday reading topics, which you found independently and read.

Your knowledge of readings will be assessed on quizzes and in-class participation, as well as exam(s).

Project: A research project, paper and presentation, will due at the end of the semester; the project/paper will be modeled on a conference paper and presentation. I don’t expect you to have a conference-worthy (or journal worthy) paper at the end of a core graduate class, but I do expect that your paper will be on a trajectory towards a project/paper worthy of publication. If I and/or your other classmates contribute significantly to the ideas and development of a project, then presumably any such paper would be coauthor(s) of the eventual submission, but for the class, you’ll be submitting a project/paper for which you are unambiguously the main author. Unless you get an exception from me, your paper/presentation will involve a substantial computer implementation of some kind. The programming language for this implementation is your choice.

In the latter part of the semester, some class sessions will be spent rotating through informal presentations by students on their projects, to include design and code reviews, and summaries of readings that students find related to their project.

Educational Video on Basic Material: You must be familiar with the material covered in CS x260 (see https://my.vanderbilt.edu/cs4260cs5260/ ).  As part of this “basics” component, you will script and video a lesson/lecture that could be used for CS x260 (Due late March or early April).

Quizzes: Quizzes will typically be given on Mondays at the start of class, or online (Brightspace), but on occasion will be given on Wednesdays if there is a reading to be done before Wednesday class.

Other assignments: The educational video will count as an assignment, as will the book review, and there will be additional assignments, at least two of which involve programming in your choice of language.

Exam(s): includes a final exam and potentially a midterm shortly after Spring break. Questions on the exam(s) will be similar to questions you might expect on the Preliminary Exam for PhD students).

Grading: Weights will be roughly 20% exam(s), 20% participation, 20% quizzes, 20% project, and 20% assignments, programming and otherwise (to include the educational video).

Attendance is required, unless stated otherwise, and is counted under the participation grade.

Honor Code: Work on exams and quizzes are to be entirely your own. Work on assignments and projects are to be primarily your own, but you can consult with others as long as you state precisely the nature of the consultation at the top of your submission file to Brightspace. You are free to consult with others on the readings.

 

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