Course Syllabus
SEN 985 Artificial Intelligence
Fall 2012 – Class Meets: Oct 19/20/21 and Nov 9/10/11
(9:00 AM - 6:00 PM) in Room 102
Instructor
Name: Barbara Hecker, PhD
Primary Email: bhecker@edu.edu
Alternative Email: bhecker@acm.org
Course Description
This course introduces the foundation of simulating or creating
intelligence from a computational point of view. It covers the
techniques of reduction, reasoning, problem solving, knowledge
representation, and machine learning. In addition, it covers
applications of decision trees, neural networks, support vector
machines and other learning paradigms.
Course Objectives
All serious programmers and software engineers should know about
the major Artificial Intelligence techniques, which are regarded by
many as the core knowledge of any Computer Science degree. This
course will allow you to gain generic problem solving skills that have
applicability to a wide range of real-world problems. Topics covered
include search, knowledge representation, Bayesian networks,
planning, expert systems, intelligent agents, and evolutionary
computation.
Learning Outcomes
After completing this course, you should be able to:
1. Describe the key components of the artificial intelligence field.
2. Describe search strategies and solve problems by applying a
suitable search method.
3. Describe and apply knowledge representation.
4. Describe and apply probability theorem and Bayesian networks.
5. Describe the key aspects of intelligent agents and Machine
Learning
Required Materials
Stuart, Russell and Norvig, Peter (2010). Artificial Intelligence: A
Modern Approach (3rd Edition). Upper Saddle River, NJ: Prentice
Hall, ISBN 0-13-604259-7.
Grading
Final Exam
20% There will be one comprehensive final exam,
which will count for 20% of your course
grade. The final exam will be given during
the scheduled final exam period.
CSLO
10% Course Student Learning Objective Essay
Take Home
Assignments
24% You will be assigned 6 AI “hands-on”
assignments throughout the term. Each
assignment will be worth 4% of your course
grade.
In Class
Assignments
36% You will be required to participate in 12 in-class
workshop exercises worth 3 points each. The
exercises can only be completed in-class during
the weekend class meeting.
Midterm
Exam
10% There will be one midterm exam about halfway through the course. This will be a takehome research project that will need to be
completed and submitted by each student.
Academic Dishonesty
Your assignments should be done without consultation with other
students (or the Internet) and you should not share your work with
others. Any assignment submitted that is essentially the same as
someone else’s will not receive credit. Any student who commits
plagiarism in any form on any assignment in this class will
automatically fail the class. NO make-up or replacement work will be
available.
Attendance Requirement
Attendance is MANDATORY on all three days for both weekends of the
class. The class will run from 9AM to 6PM. Plan to be in San Jose on
Friday at 9am. Late arrival on the first day is not acceptable. The class
will end at 6pm on Sunday night. Early departure Sunday afternoon
will not be acceptable. You are REQUIRED to arrange your travel to
accommodate full attendance of the weekend class.
Any student who fails to attend any day of the class either in the first
or second weekend will automatically FAIL the class no matter what
work has been submitted.
Grading Formula
A
95 – 100
C+
77 – 79
A-
90 – 94
C
73 – 76
B+
87 – 89
C-
70 – 72
B
83 – 86
D
60 – 69
B-
80 – 82
F
59 or <
Class Meeting Format
Each day of this class will meet 9am to 6pm with a 1 hour break from
12 noon to 1pm.
This class will be conducted in a workshop format. ALL students MUST
bring a computer with them, Mac or PC.
There will be 4 hours of lecture and 4 hours of lab work each day. The
lab work will be conducted in class ONLY. At the end of the day (by
6pm) all work must be submitted to the ITU EMS for grading. The lab
work cannot be performed outside of class. Workshop lab assignments
will not be available before or after the weekend meetings therefore it
is imperative that each student brings the necessary equipment (a
computer) and actively participates in the workshop exercises during
the day of each class meeting.
All students should verify ITU EMS access prior to the first weekend
class meeting.
Weekend Course Schedule
Weekend 1 - Oct 19/20/21
Friday Oct 19th
Friday Morning Session (9am - 12noon):
9am to 9:15am
9:15am to 11am
11 to Noon
12 Noon to 1pm
Attendance Check-in
Chapter 1 - Course Overview and Introduction
Chapter 2 - Intelligent Agents
In-Class - Lab Exercise 1 – Submitted to EMS
LUNCH BREAK
Friday Afternoon Session (1pm – 6pm):
1pm to 3pm
3pm to 4:30pm
4:30pm to 6pm
Chapter 3 – Problem Solving and Search
In-Class - Lab Exercise 2 – Submitted to EMS
Review of Lab Exercises 1 and 2
Chapter 3 – Problem Solving and Search
Saturday Oct 20th
Saturday Morning Session (9am - 12noon):
9am to 9-15am
9:15 to 11am
11 to Noon
12 Noon to 1pm
Attendance Check-in
Chapter 4 - Informed Search
In-Class - Lab Exercise 3 – Submitted to EMS
LUNCH BREAK
Saturday Afternoon Session (1pm - 6pm):
1pm to 3pm
3pm to 4:30pm
4:30pm to 6pm
Chapter 4 - Informed Search
In-Class - Lab Exercise 4 – Submitted to EMS
Review of Lab Exercises 3 and 4
Chapter 5 – Game Playing
Sunday Oct 21st
Sunday Morning Session (9am - 12noon):
9am to 9:15am
9:15am to 11am
11 to Noon
12 Noon to 1pm
Attendance Check-in
Chapter 6 - Agents that Reason Logically I
In-Class - Lab Exercise 5 – Submitted to EMS
LUNCH BREAK
Sunday Afternoon Session (1pm – 6pm):
1pm to 3pm
3pm to 4:30pm
4:30pm to 6pm
Chapter 6 - Agents that Reason Logically II
In-Class - Lab Exercise 6 – Submitted to EMS
Review of Lab Exercises 5 and 6
Midterm Exam Review
NOTE: The midterm exam will be handed out at the end of the first
weekend. It is due, posted in the EMS by November 8th, late midterm
exams will not be accepted.
Homework assignments 1, 2, 3 and 4 are due on November 8th before
the start of the second weekend class meeting.
Weekend 2 - Nov 9/10/11
Friday November 9th
Friday Morning Session (9am -12noon):
9am to 9:15am
9:15am to 11am
11 to Noon
12 Noon to 1pm
Attendance Check-in
Chapter 7 – First Order Logic
In-Class - Lab Exercise 7
LUNCH BREAK
Friday Afternoon Session (1pm - 6pm):
1pm to 3pm
3pm to 4:30pm
4:30pm to 6pm
Chapter 8 – Building a Knowledge Base
In-Class - Lab Exercise 8
Review of Lab Exercises 7 and 8
Chapter 8 - Building a Knowledge Base
Saturday November 10th
Saturday Morning Session (9am – 12noon):
9am to 9:15am
9:15am to 11am
11 to Noon
12 Noon to 1pm
Attendance Check-in
Chapter 9 - Inference in First-Order Logic
In-Class - Lab Exercise 9
LUNCH BREAK
Saturday Afternoon Session (1pm – 6pm):
1pm to 3pm
3pm to 4:30pm
4:30pm to 6pm
Chapter 9 - Inference in First-Order Logic
In-Class - Lab Exercise 10
Review of Lab Exercises 9 and 10
Chapter 10 - Logical Reasoning Systems
Sunday November 11th
Sunday Morning Session (9am – 12noon):
9am to 9:15am
9:15am to 11am
11 to Noon
12 Noon to 1pm
Attendance Check-in
Fuzzy Logic
Chapter 11 – Planning
Expert Systems
In-Class - Lab Exercise 11
LUNCH BREAK
Sunday Afternoon Session (1pm – 6pm):
1pm to 3pm
3pm to 6pm
In-Class – Lab Exercise 12
In-Class – Final Exam
NOTE: The final exam will be conducted at the end of the second
weekend starting at 3pm on Sunday. This exam must be taken in class
and cannot be made up at a later date.
Homework assignments 5, 6 and the CSLO Essay are due on
December 14th.