CS 580 - 610

Introduction to Artificial Intelligence

Meets

Tuesday 4:30 pm - 7:10 pm ONLINE

Office hours

Professor

Zoran Duric.

Course Web Page

All course materials including slides, homeworks, and projects will be posted on the course blackboard page. We will use the blackboard discussion forum.

Textbook

Artificial Intelligence: A Modern Approach, 4th ed., Russell & Norvig, Prentice Hall

Supplementary texts

Prerequisites

A working knowledge of computer systems and several programming languages is required. The material covered in CS 310 (or INFS 519/CS 531) and CS 330 (or CS 530) as well as general computer science maturity is assumed and used throughout the course.

Content

The course can be roughly divided in two parts: (i) Intelligence from computation including uninformed and informed search, adverserial search, constraint satisfaction, markov decison processes, and reinforcement learning; (ii) Intelligence from data including probailistic reasoning, and unsupervised and supervised machine learning methods.The Python programming language will be used as the primary language for homework assignments.

Exams

There will be a midterm and final exam.

Homework

There will be several programming assignments which will include written summaries. Other assignments could include practice problems from the textbook and/or old exams.

Grading

The course grade will be determined approximately as follows:

Individual work

You are free to discuss ideas for both the labs and projects with other students, however no joint work is permitted unless explicitely stated in the assignment. Any submitted work must be yours alone. Any work which shows too much similarity with others' submitted work will receive a grade of 0. Extreme or repeat cases may result in failing the course or referral to the Honor Commitee.

Read the CS Department honor code and the University honor code. You are bound by these honor codes.