Download De La Salle University • College of Computer Studies Course

De La Salle University • College of Computer Studies
Course Syllabus
INTROAI / Introduction to Artificial Intelligence
Prerequisites
Type of Course
Faculty
:
:
:
Term
:
DISCTRU
Basic course
Dr. Raymund Sison
[email protected]
http://mysite.dlsu.edu.ph/faculty/sisonr/#Teaching
Term 1 AY 2010-11
Course Description:
Artificial Intelligence (AI) is the study of how machines can exhibit at least one of the following aspects
associated with intelligent behavior: (a) problem solving, or the performance of non-trivial, goal-directed
cognitive tasks even in the face of inadequate (e.g., incomplete, incorrect, inconsistent, or vague) data; (b)
reasoning, or the drawing of logical inferences and conclusions from possibly inadequate evidence; and (c)
learning, or the improvement of performance through experience. This 3.0-unit course introduces the CS-ST
major to fundamental concepts, principles, and techniques in search-based problem solving, reasoning, and
machine learning, and in the representation of the knowledge needed to perform these tasks.
Objectives / Values:
At the end of the course, students should be able to:
1. Describe the basic approaches to search and knowledge representation;
2. Analyze algorithms and higher-level control regimes for searching problem spaces;
3. Model knowledge from different domains using various knowledge representation schemes;
4. Analyze and compare the two most important approaches to machine learning; and
5. Build small to medium-sized intelligent applications using the AI representations and techniques that
they have learned.
Throughout the course, students are expected to practice the Lasallian values, particularly the values of zeal
and love for one’s community (in this case, one’s class and group), by:
6. Preparing well for, and participating actively, in class;
7. Listening and speaking to others, whether the professor or a classmate, with respect; and
8. Cooperating and collaborating well with one’s group mates.
Topics and Calendar:
Week
Topics
1
Course Requirements
AI Definition, History, and Overview
2
Search: Basic Algorithms
3
Search: Heuristics
4
Search: Game Trees
5
Representation: Propositional Logic
6
Representation: Predicate Logic
7
Reasoning: PROLOG (PROgramming in LOGic)
8
Reasoning: Rule-based Expert Systems
Readings
AIMA2E*Chapter 1
AIMA2E Chapter 3
AIMA2E Chapter 4
AIMA2E Chapter 6
AIMA2E Chapter 7
AIMA2E Chapter 8
(Blackburn et al, 2006)
Chapter 8 of (Luger, 2005)
Deadlines
Student info
sheet & ID pic
Assignment 1**
Exam 1
1 of 3
Week
9
10
11
12
13
Topics
Reasoning: Uncertainty***
Machine Learning: Decision Trees
Machine Learning: Neural Networks
Philosophy of AI
Integration
Readings
Section 9.2 of (Luger, 2005)
AIMA2E Chapter 18
AIMA2E Chapter 20
AIMA2E Chapter 26
Deadlines
Assignment 2**
Exam 2
Assignment 3**
Assignment 4**
(can be earlier)
Notes:
* AIMA2E stands for “Artificial Intelligence: A Modern Approach, 2nd Ed” by Russell and Norvig (see Text
below).
** A soft copy of this document will be e-mailed to the professor before 9:00 AM of the Monday of the specified
week. Late submissions will incur a 1-point deduction per day late (excluding Sundays). The General Report
Formatting Guidelines are on a separate document, downloadable from the professor’s website.
*** This topic is a reading assignment, for which there will be no lecture.
Teaching Methods / Strategies:
Lectures
Discussions
Recitations
Written reports
Assignments
Group projects
Requirements:
This course has 3 kinds of requirements: class participation, exams, and assignments.
Class participation (recitation, snap quizzes, special oral reports)

Students may accumulate up to 20 points through class participation. You can view your class
participation scores at http://mysite.dlsu.edu.ph/faculty/sisonr/#Teaching.

Students who recite must e-mail the professor within the day the number of points and questions
answered. The subject of the e-mail must be: INTROAI - Recitation - <section> - <points> - <last name
if not on e-mail address> <first name if not on -mail address>. For example: INTROAI - Recitation - S17
- 1 - Sison Raymund. In the body of the e-mail, specify your name (last name first), the question asked
by the professor, and the answer that you gave.

The slides of any special oral reports must use the masters of the slides of this course, and must be emailed, with corrections, to the professor within 24 hours of the oral presentation. The subject of the email must be: INTROAI - Special Report - <section> - <last_name> <first_name>. For example:
INTROAI - Special Report - S17 - Sison Raymund.
Exams

There will be two exams. The first exam will cover search and representation; the second will cover
reasoning and machine learning. The weeks of these exams are specified in the course calendar
above. The exact dates and times will be determined by the professor and students on the first week of
classes.
Assignments

The deadlines of the course’s four assignments are specified in the course calendar above. The specs
of these assignments will be provided on the second week of classes.
Assessment / Evaluation:
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To pass this course, one must accumulate at least 60 points through the course requirements discussed
above. The maximum points that a student can obtain through each requirement are shown below.
Assessment Task
Class Participation
Exam 1
Exam 2
Assignment 1 (AI Cap’n)
Assignment 2 (Knowledge Base)
Assignment 3 (Machine Learning)
Assignment 4 (AI Applications)
TOTAL POINTS
Maximum
points
20
15
15
10
15
15
10
100
Text / Materials:
Russell, S. and Norvig, P. (2003). Artificial Intelligence: A Modern Approach, 2nd Ed. New Jersey: PrenticeHall.
This is the AI textbook used by top Computer Science departments in the world. A low price edition (with a
green soft cover) is available in Philippine bookstores. There are also a few copies at the DLSU library; two
of these have been placed in the Circulation-Reserve section.
References:
Blackburn, P., Bos, J. & Striegnitz, K. (2006). Learn Prolog Now! UK: College Publications.
There is a free online version of this book at: http://www.learnprolognow.org/.
Jones, M. T. (2008). Artificial Intelligence: A Systems Approach. Hingham, Massachusetts: Infinity Science.
This is the newest book to be titled “Artificial Intelligence”. It is easier to read but is less comprehensive than
both (Russell & Norvig, 2003) and (Luger, 2005). It also contains C implementations of the basic AI
algorithms. A copy is available at the DLSU library, and has been placed in the Circulation-Reserve section.
Luger, G. (2005). Artificial Intelligence: Structures and Strategies for Complex Problem Solving, 5th Ed. Harlow,
Essex: Addison-Wesley.
This is easier to read than (Russell & Norvig, 2003). The fourth edition of this book is available at the DLSU
library and has been placed in the Circulation-Reserve section. Also available in Philippine bookstores.
General Report Formatting Guidelines
The General Report Formatting Guidelines are on a separate document, downloadable from the professor’s
website. When submitting any written documents in this course, these guidelines must be adhered to.
Nonadherence to a guideline will merit deductions.
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