COURSE DESCRIPTION:
This is an introductory graduate AI course.
During the first part of the semester we will cover general
knowledge representation techniques and problem solving strategies.
Topics will include
intelligent agents,
search,
game playing,
constraint satisfaction,
rule-based systems,
logic-based systems,
logic programming,
planning,
reasoning with uncertainty,
and probabilistic reasoning.
During the second part of the semester we will discuss three important
application areas in AI: machine learning, natural
language processing, and machine vision, as well as their use in robotics.
For the catalog description of this course
see the WPI Graduate Catalog.
CLASS MEETING:
Mondays and Wednesdays: 11 am - 12:20 pm.
Classrooms:
- AK233: January - February, 2019
- FL320: March - April, 2019
INSTRUCTOR:
Prof. Carolina Ruiz
Office: FL 232
Office Hours:
- Mondays: At the end of class: 12:20-1:00 pm.
- Wednesdays: At the end of class: 12:20-1:00 pm.
- Fridays: 1:00 - 2:00 pm.
- If you need to see me at a different time,
please email me to schedule an appointment.
Sanket Gujar, Computer Science Graduate Student
Office Hours:
- Mondays: 10-11 am. Fuller Labs Sub-basement Room A22.
- Tuesdays: 3-4 pm. Fuller Labs Sub-basement Room A22.
- Thursdays: 11-12 noon. Fuller Labs Sub-basement Room A22.
- If you need to see Sanket at a different time, email him to schedule an appointment.
TEXTBOOK:
RECOMMENDED BACKGROUND:
Familiarity with data structures and a recursive high-level language.
GRADES:
| Exam 1 | 25%
|
| Exam 2 | 25%
|
| Project | 20%
|
| Homework | 20% (lowest hw grade will be eliminated)
|
| AI Showcase | 8%
|
| Class Participation | 2%
|
Your final grade will reflect your own work and achievements
during the course. Students are expected to follow
WPI's Academic Honesty Policy.
Students are expected to read the material assigned to each
class in advance and to participate in class.
Class participation will be part of students' final grades.
Note that this course follows the guidelines established by
the WPI faculty in May 2010:
"A student is expected to expend at least 56 hours of total effort for
each graduate credit. This means that a student in a 3-graduate credit
14-week course is expected to expend at least 12 hours of total effort
per week."
Hence, please expect to have to spend at least 9 hours of work outside the
classroom on this course each week.
EXAMS
There will be a total of 2 exams. Each exam will cover the
material presented in class since the beginning of the course.
In particular, the final exam is cumulative.
Makeup Exams
Regarding makeup exams,
I follow Prof. Gennert's policy:
"Makeup and/or early examinations are not given except under the most
dire of circumstances, and then only with corroborating documentation.
Note well that neither oversleeping, forgetting to show up for an exam,
nor conflicting travel arrangements are considered dire circumstances."
HOMEWORK, PROJECT, AND SHOWCASE
Homework
There will be several homework assignments during the semester.
The homework statements will be posted on the course webpage.
Submission deadlines and instructions will be posted on each homework webpage.
Students should be prepared to present and discuss
their homework solutions in class.
No extensions to homework submission deadlines will be granted and
no late homework submissions will be accepted. No exceptions.
Please plan accordingly.
Project
There will be one major course project. This project may consist of several
smaller parts.
A detailed description of the project will be posted to the course webpage
at the appropriate time during the semester.
Although you may find similar programs/systems available online or in the
references,
the design and all code you use and submit for you projects MUST be your own original work.
No extensions to project submission deadlines will be granted and
no late project submissions will be accepted. No exceptions.
Please plan accordingly.
Showcase
Each student needs to sign up for one of the available
showcase topics.
The team of students assigned to a showcase topic should follow
the instructions on the showcase webpage to select
a real-world, successful application of the AI topic,
prepare slides and present the showcase in class according to the
showcase schedule.
- Class Discussion Boards:
The main digital venue for communication outside the classroom will be the
CS534 Discussion Boards provided by Canvas. To access these discussion forums,
go to Canvas,
click "CS534-S19-191: ARTIFICIAL INTELLIGENCE" under "My Courses",
and then click on "Discussions" on the left hand-side bar.
- Class Mailing List:
There is also a mailing list for this class available on Canvas that will be used by the professor for general announcements,
but not for class discussions as all class discussions will be on Canvas Discussion Boards.
Please make sure to read Canvas CS534 discussion boards and emails sent to the class mailing list constantly throughout the semester so that you don't miss any important course information.
CLASS WEB PAGES
The web pages for this class are located at
https://web.cs.wpi.edu/~cs534/s19/
Announcements will be posted on the web pages and/or
the class mailing list, and so you are urged to check your WPI email and
the class web pages frequently.
WARNING:
Small changes to this syllabus may be made during the course
of the term.
ADDITIONAL SUGGESTED REFERENCES
See my list of additional
AI, Machine Learning, Data Mining, Statistics, Databases, Data Sets and other online resources.
OTHER AI RESOURCES ONLINE:
