University of Ontario Institute of Technology
Faculty of Engineering and Applied Science
ENGR3720U: Introduction to Artificial Intelligence.
COURSE OUTLINE
Course Objectives
This course introduces students to basic concepts and methods of artificial intelligence from a
software engineering perspective. Emphasis of the course will be on the selection of data
representations and algorithms useful in the design and implementation of intelligent systems.
Knowledge representation methods, state space search strategies, and use of logic for problem
solving. Applications chosen from among expert systems, planning, natural language
understanding, uncertainty reasoning, machine learning, and robotics. The course will contain an
overview of one AI language and discussion of important applications of artificial intelligence
methodology.
Course Outcomes
At the end of the course the students should be familiar with …
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Data representations and algorithms useful in the design and implementation of intelligent
systems.
Knowledge representation methods.
State space search strategies.
Use of logic for problem solving.
Artificial intelligence as applied to expert systems, planning, uncertainty reasoning, machine
learning, and robotics.
Overview of Prolog or LISP.
Prerequisites
ENGR 3770U: Design and Analysis of Algorithms.
Course Organization
Three lecture hours and three hour tutorials per week for one semester.
Required Course Texts and Other Materials
Textbook:
Artificial Intelligence A Modern Approach, 2nd edition.
Stuart Russell and Peter Norvig
Publisher: Prentice Hall
Copyright: 2003
ISBN-10: 0-13-790395-2
Software Tools:
Eclipse Integrated Software Development Environment
Amzi Prolog
Lego Mindstorm NXT Robot Kits
Java Expert System Shell
Reference Books and Information Sources
Text book course web site http://aima.cs.berkley.edu
Course Evaluation
Group Project
Tutorial Quizzes
Assignments (5)
Midterm Test (1)
Final Exam
Total:
25%
5%
25%
15%
30%
100%
Detailed Course Content
Please provide main topics and brief descriptions, along with approximate durations or week
numbers, and with indication of the corresponding source material from text or other sources).
1. Chapter 1: Introduction (week 1)
2. Chapter 2: Intelligent Agents (week 1)
3. Chapter 3: Solving Problems by Searching (week 2 and 3)
4. Chapter 4: Informed Search and Exploration (week 4)
5. Chapter 6: Adversarial Search (week 5)
6. Chapter 7: Logic Agents (week 6)
7. Chapter 8: First-Order Logic (week 7)
8. Chapter 9: Inference in First-Order Logic (week 8)
9. Chapter 10: Knowledge Representation (week 9)
10. Chapter 11: Planning (week 10)
11. Chapter 13: Uncertainty (week 11)
12. Chapter 14: Probabilistic Reasoning (week 12)
13. Chapter 18: Learning from Observation (week 13)
Laboratories
Not Applicable
Tutorials
Tutorials are 3 hrs long and will typically be divided into 3 parts.
a)
Review of tutorial questions (1 hr 20 min), followed by a break.
b)
Short quiz questions (20 min)
c)
Agent / Robot training (1 hr)
The review and quizzes reflect questions similar to those in an exam. The Agent / Robot training is
used to introduce the students to Agent programming and the NXT robot programming that they will
use for their project.
Computer Experience
The Eclipse IDE and Prolog Programming language will be extensively used by students.
Course Content Breakdown
(following categories defined by the Canadian Engineering Accreditation Board’s Accreditation
Criteria and Procedures report, available at http://ccpe.ca/e/files/report_ceab.pdf)
Mathematics:
Basic Science:
Engineering Science:
Engineering Design:
Complementary Studies:
Total:
5%
5%
40%
50%
0%
100%
Other Information
Engineering design is enforced primarily through a significant group project that demonstrates
the coordination of robots by leveraging agent-based languages and platforms.
SOME IMPORTANT GENERAL INFORMATION OF RELEVANCE TO THE COURSE
Academic Integrity and Conduct
UOIT is committed to the fundamental values of preserving academic integrity as defined in
UOIT policies and contained in the UOIT Calendar. Students should familiarize themselves with
UOIT’s policies and statements in this area. Acts of academic dishonesty, including plagiarism,
cheating, aiding others in cheating, and examination impersonation, will be dealt with severely as
they threaten the integrity of the academic system and are not acceptable.
UOIT and faculty members reserve the right to use electronic means to detect and help prevent
plagiarism. Students agree that by taking this course all assignments are subject to submission for
textual similarity review to Turnitin.com. Assignments submitted to Turnitin.com will be
included as source documents in Turnitin.com's restricted access database solely for the purpose
of detecting plagiarism in such documents for five academic years. The faculty member may
require students to submit their assignments electronically to Turnitin.com or the faculty member
may submit questionable text on behalf of a student. The terms that apply to UOIT's use of the
Turnitin.com service are described on the Turnitin.com website. (To read the entire policy, please
go to: http://www.uoit.ca/EN/main2/11246/13525/14057/14152/turnitin_policy.html.)
Accessibility
To insure that disability-related concerns are properly addressed during this course, students with
documented disabilities and who may require assistance to participate in this class are
encouraged to speak with their instructor as soon as possible. Students who suspect they may
have a disability that may effect their participation in this course are advised to go to the Centre
for Students with Disabilities (room B297) as soon as possible.
Approved by (indicating approval of Faculty’s Curriculum Committee):
Mikael Eklund (Program Director)
Date: