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NEWS
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   Jun 7th
    2012
Dean's scholarship awarded
The Dean's scholarship of the Faculty of Graduate and Postdoctoral Studies of the University of Ottawa has been awarded.

 May 24th
     2012
Conference paper accepted
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
Conference paper accepted
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
Conference paper accepted
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
Successful PhD thesis defense
Rafael has successfully defended his doctoral thesis entitled "Towards Fault Reactiveness in Wireless Sensor Networks with Mobile Carrier Robots"

   Feb 7th
    2012
NSERC IRDF Fellowship awarded
Industrial Research & Development Fellowship (IRDF) awarded by the Natural Sciences & Engineering Research Council (NSERC) with Larus Technologies Corporation as the industrial partner.

 
CSI4106 Introduction to Artificial Intelligence
 
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
  • Professor's permission

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)
    • Study break
  • 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)
  • Week 14 (April 8 - 12, 2013)
    • Presentation Session (4 presentations)
  • Final Exam: Monday April 22nd, 2013, 14:00 - 17:00
    • Location TBA

 
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