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NEWS |
( view all)
Jun 7th
2012
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Dean's
scholarship awarded
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The
Dean's scholarship of the
Faculty of Graduate and
Postdoctoral Studies of the
University of Ottawa has
been awarded.
May 24th
2012 |
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Conference
paper accepted
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The paper " An
Online Shadowed Clustering
Algorithm Applied to Risk
Visualization in Territorial
Security" has been
accepted for presentation at
the 2012 IEEE Symposium on
Computational Intelligence for
Security and Defense
Applications ( CISDA
2012).
Mar 22th
2012
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Conference
paper accepted
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The
paper " Controlled
Straight Mobility and
Energy-Aware Routing in
Robotic Wireless Sensor
Networks" has been
accepted for presentation at
the 2012 IEEE International
Conference on Distributed
Computing in Sensor Systems
( DCOSS
2012), Hangzhou,
China.
Feb
21th
2012
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Conference
paper accepted
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The
paper " A Response-Aware
Risk Management Framework
for Search-and-Rescue
Operations" has
been accepted for
presentation at the 2012
IEEE Congress on
Evolutionary Computation ( CEC
2012), Brisbane,
Australia.
Feb
13th
2012
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Successful
PhD thesis defense
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Rafael
has successfully defended
his doctoral thesis entitled
" Towards Fault
Reactiveness in Wireless
Sensor Networks with
Mobile Carrier Robots"
Feb 7th
2012
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NSERC IRDF
Fellowship awarded
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CSI4106 Introduction to Artificial Intelligence
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Announcements:
- Mar
16th:
Assignment 3
is now posted
on Virtual
Campus!
- Mar
13th:
Presentation
schedule
updated! Check
the latest
version in
Virtual
Campus!
- Mar
7th: Final
Exam on Monday
April 22nd,
14:00 - 17:00
location TBA!
- Feb
27th:
Presentation
schedule is
now posted!
- Feb
27th:
Assignment 1
marks and
Prolog
solution are
now posted!
- Feb
18th:
Assignment 2
is now posted!
Deadline:
March 13th,
22:00.
- Feb
18th: Midterm
marks and
solutions are
now posted!
- Jan 26th: Project
topics have
been assigned!
Check your
inbox.
- Jan 22th: Assignment 1 is now posted! Deadline: February
7th, 15:00
- Jan 19th: Research project guidelines are now available
in Virtual Campus
Description:
- The
roots and
scope of
Artificial
Intelligence.
- Knowledge
representation.
- Search,
informed
search,
adversarial
search.
- Deduction
and
reasoning.
- Uncertainty
management.
- Introduction
to Natural
Language
Processing.
- Elements
of planning.
- Basics
of Machine
Learning and
Expert
Systems.
Objectives:
When
you complete
this course,
you will be
able to:
- Understand
the
terminology
and the
techniques
currently in
use in the
field of
Artificial
Intelligence
(AI).
- Consider
a complex
problem and
find a way to
represent it
in a form
compatible for
computer
processing.
- Apply
or design an
appropriate
technique for
solving this
problem with
moderate or no
user
intervention.
- Have
a broad-level
picture of the
main AI
application
areas.
Prerequisites:
- MAT1348
(Discrete
Mathematics
for Computing)
and
- CSI3120
(Programming
Languages
Concepts) or
- SEG2106
(Software
Construction)
or
Schedule:
- Lecture
1:
Monday 14:30 -
16:00 (SITE
C-0136)
- Lecture
2:
Thursday 16:00
- 17:30
(Lamoureux
106)
- Office
hours:
Monday 16:00 -
17:00 (SITE
0110-B)
Textbook:
- Official
textbook:
George F.
Luger: "Artificial
Intelligence:
Structures and
Strategies for
Complex
Problem
Solving",
6th Edition,
Addison
Wesley, 2009
(available at
the Agora
bookstore
for ~ $150)
- Alternatively,
you may buy
the 5th
edition of the
same book
(available at
Amazon
for ~ $40).
- Alternative
textbook:
Stuart Russell
and Peter
Norvig: "Artificial
Intelligence:
A Modern
Approach",
3rd Edition,
Pearson, 2010
- Optional:
For learning
Prolog (very
useful for
your
assignments),
you may
consider "Prolog
Programming
for Artificial
Intelligence,
4th Edition"
by Ivan Bratko
(available at
the Agora
bookstore)
Evaluation:
- Assignments
(30% = 3 x 10%
each)
- Project
Report/Presentation
(15%)
- Midterm
Exam (20%)
- Final
Exam (35%)
Assignments:
- To
be done
individually.
- Posted
about two
weeks before
their due
date.
- Must
be handed in
at the
beginning of
the class, on
their due day.
- There
are no make-up
assignments.
Presentation
& Report:
Students,
in
teams of two,
will conduct a
research
project on
methodologies,
tools and
practical
applications
of Artificial
Intelligence.
This will
involve:
- Carrying
out research
on the topic
of the team's
choice
- Submitting
a report on
this research
and
- Giving
a presentation
to the class,
during which
both team
members will
have to speak.
You
may choose a
topic from the
list available
in the project
guidelines on
Virtual Campus.
Exams:
There
will be two
exams: a
midterm and a
final. These
are the dates:
- Midterm:
Thu
February 14,
16:00 - 17:30,
ART 257
- Final:
TBA
Other
important
aspects:
- It
is compulsory
to write the
midterm exam.
- There
will be NO
make-up
midterm exam.
- If
you have a
valid medical
reason to
justify your
absence from
the midterm
(and confirmed
by the
University
Health
Services),
your 20% value
of the midterm
will be
transferred to
the final exam
(so it will be
now worth
55%).
- Failure
to write the
midterm for
any other
reason without
the consent of
the course
instructor
will imply a
mark of 0.
Marking
Scheme:
- Assignments
(30% = 3 x
10%)
- Project
Report &
Presentation
(15%)
- Midterm
Exam (20%)
- Final
Exam (35%)
To
pass the
course, you
must pass all
its
examination
exercises.
That is, you
must achieve
at least 50%
(27.5 marks
out of 55)
between the
midterm and
the final
exams.
Otherwise,
your mark out
of 55 will be
converted to a
mark out of
100 and your
final grade
will be either
E or F.
Materials:
All
the course
slides, a
description of
plagiarism and
its
consequences,
as well as
your
assignments
and other
relevant
materials are
accessible
through Virtual Campus.
Syllabus:
- Week
01 (January 7
- 11, 2013)
- What
is Artificial
Intelligence?
- Knowledge
Representation
and Search
- Week
02 (January 14
- 18, 2013)
- Uninformed
Search
- Heuristic
Search
- Week
03 (January 21
- 25, 2013)
- Adversarial
Search (Games)
- Logic-based
Representational
Systems (I)
- Assignment
1 posted
- Week
04 (January 28
- February 1,
2013)
- Logic-based
Representational
Systems (II)
- Logic-based
Representational
Systems (III)
- Week
05 (February 4
- 8, 2013)
- Deductive
Reasoning
- Other
Knowledge
Representation
Systems
- Week
06 (February
11 - 15, 2013)
- Expert
Systems /
Midterm Review
- Midterm
Exam (Feb 14,
16:00 - 17:30,
ART 257)
- Assignment
2 posted
- Week
07 (February
18 - 22, 2013)
- Week
08 (February
25 - March 1,
2013)
- Expert
Systems
(cont'd) /
Representing
Uncertain
Knowledge
- Machine
Learning (I)
- Week
09 (March 4 -
8, 2013)
- Machine
Learning (II)
- Machine
Learning (III)
- Tools
- Presentation
Session (1
presentation)
- Week
10 (March 11 -
15, 2013)
- Natural
Language
Processing (I)
- Natural
Language
Processing
(II)
- Assignment
3 posted
- Week
11 (March 18 -
22, 2013)
- Course
Evaluation /
Final Exam
Review / IEEE
Student Branch
- Presentation
Session (4
presentations)
- Week
12 (March 25 -
29, 2013)
- Presentation
Session (3
presentations)
- Presentation
Session (4
presentations)
- Week
13 (April 1 -
5, 2013)
- Easter
Monday (no
class)
- Presentation
Session (4
presentations)
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- Week
14 (April 8 -
12, 2013)
- Presentation
Session (4
presentations)
- Final
Exam: Monday
April 22nd,
2013, 14:00 -
17:00
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