COSC 4368: Artificial Intelligence Programming, spring 2017


General Information

 

Instructor: Ricardo Vilalta (r.vilalta.us@ieee.org)

 

Office: MRE (Multidisciplinary Research and Engineering) Bldg., Room 203C

 

Telephone: (713) 743-3614

 

Office Hours: Mondays 11:00 AM to 12:00 PM

 

Class room: CBB Bldg., Room 124

 

Meeting Time: Mondays and Wednesdays 1:00 - 2:30 PM.

 

Textbook: Artificial Intelligence A Modern Approach

by Stuart Russell and Peter Norvig. 3rd Edition, Prentice Hall, 2010.

 

 


Information TAs (Teacher Assistants)

 

 

Zahra Pisheh

Dainis Boumber

 

Office: TBD

 

Office Hours: TBD

 

Email: zpisheh@uh.edu

 

Office: TBD

 

Office Hours: TBD

 

Email: dainis.boumber@gmail.com

 

 


Course Description

 

Artificial Intelligence is the study of how to embed intelligent behavior in machines. The field is relatively young (since middle 20th century) and it is not until recently that it has experienced an increase in maturity as seen by a more rigorous and formal approach to its methodology. In this course, we will cover fundamentals aspects of artificial intelligence in a broad and general fashion. The class will be self-contained (i.e., I will not assume any previous knowledge). Main topics include problem solving, knowledge and reasoning using first order logic, planning, uncertain and probabilistic reasoning, learning, and robotics. 

 

 


Grading

 

 

Graded Work

Weight

2 Midterm Exams

60%

Homework

20%

Project

20%

 

 


Calendar

 

 

 

Dates to remember

Events

January 18

First day of classes

March 6

1st Midterm Exam

March 13-18

No Class (Spring Holiday)

April 24

2nd Midterm Exam

Note: There is no final exam in this course.

 

 


Schedule

 

 

Dates

Topic

January 18

Introduction

 

January 23

Problem Solving

January 30

Logical Agents

February 6

First-Order Logic

February 13

Probabilistic Reasoning

February 20

Planning

February 27

Making Decisions

March 6

1st Midterm Exam

March 13

Spring Holiday -- No Class

March 20

Machine Learning I

March 27

Machine Learning II

April 3

Machine Learning III

April 10

Reinforcement leaning

April 17

Perception and Robotics

April 24

2nd Midterm Exam

May 1

Final Project Due

 


Files for Downloading and Additional Class Information

 

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