CP468 ARTIFICIAL INTELLIGENCE, FALL 2024, WLU

Course Description

Prerequisites

Instructor

Important Course Information

Office Hours

• Please e-mail me to book an individual appointment at my office or on skype/zoom.
• For authentication/security purposes, please include your Laurier Student ID, and your first and last name, in all communcations regarding the course.

Course Textbook

Textbook Support Website http://aima.cs.berkeley.edu

Lecture Topics (corresponding to the 12 weeks schedule)

1. Introduction, Intelligent Agents
2. Problem solving, searching
3. Metaheuristics I: Local Search, Tabu Search, Hill Climbing
4. Metaheuristics II: Simulated Annealing, Genetic Algorithms, Ant Colony Optimization
5. Constraint Satisfaction Problems
6. Automated Reasoning, Prolog
7. Knowledge Representation
8. Knowledge-based systems
9. Machine Learning
10. Neural Networks I: Architectures, Pattern Classification
11. Neural Networks II: Single-layer, Multi-layer
12. Term Projects Presentations

Class Schedule and Fall Semester Timetable

              |     Mon     |     Wed     |
              | 17:30-18:50 | 17:30-18:50 |
              |    N1002    |    N1002    | 
______________|_____________|_____________}_
              |             |             |             
Week 1:       |  Sep 09     |    Sep 11   |   
Week 2:       |  Sep 16     |    Sep 18   |   
Week 3:       |  Sep 23     |    Sep 25   |   
Week 4:       |  Sep 30     |    Oct 02   |   
Week 5:       |  Oct 07     |    Oct 09   |   
______________|_____________|_____________|_
              |
Reading Week  | Oct 14-18 N o C o u r s e s
______________|_____________________________
              |             |             |            
Week 6:       |  Oct 21     |   Oct 23 M  |   
Week 7:       |  Oct 28     |   Oct 30    |   
Week 8:       |  Nov 04     |   Nov 06    |   
Week 9:       |  Nov 11     |   Nov 13    |   
Week 10:      |  Nov 18     |   Nov 20    |  
Week 11:      |  Nov 25     |   Nov 27    |  
Week 12:      |  Dec 02 TP  |   Dec 04 TP |  
______________|_____________|_____________|_
              |             |             | 

Course Requirements/Student Evaluation

• The course final grade is computed based on the 4 components: A1, A2, M, TP, explained in more detail below.

• A1, A2, TP, are groupwork. Students are required to form groups (of 10 students each) to work on A1 A2 TP collaboratively. Please designate a group member as the group rep, and have them e-mail me the first/last names and IDs/e-mails of ALL the group members. Each group will receive a number (GroupID), on a first-come-first-served basis)

• The course final grade is computed as: A1*(20/100) + A2*(20/100) + M*(30/100) + TP*(30/100)

• (A1) Assignment 1: 20%, release date: TBA, due date: TBA, (A1 is static)

• (A2) Assignment 2: 20%, release date: TBA, due date: TBA, (A2 is dynamic: live demo is required for every group)

live demo schedule: TBA (details in class) 

• (M) Midterm 30%, Oct 23, 2024 (in class)

• (TP) Term Project: 30%, Due date: Dec 06, 2024

• Important Information regarding groupwork submission:
  • Late submissions will be marked with 0.

  • All assignment submissions will be on MyLS only.

  • All assignment submissions must be typeset (LaTeX, Word).

  • All assignment submissions must be by .pdf file attachment only.

  • Please upload one .pdf file only, for the entire assignment.

  • Use the following naming schemes, for your .pdf files:
    CP468-A1-GroupID.pdf CP468-A2-GroupID.pdf CP468-TP-GroupID.zip (these are dash characters, not underscores)

  • Your submissions should have a cover page, all pages should be numbered and on each page include a header with your GroupID, course code, submission date, and A1/A2

  • Submissions that violate any of the above requirements, will not be accepted/marked.

• (TP) Term Project: 30%, due date: December 06, 2024

  All students will be required to prepare a Term Project, details in class. Each group will have to deliver a project document and conduct a project demonstration during Week 12 of classes.

Term Project Demonstrations Schedule

(You are strongly advised to upload your presentation materials on the classroom computer beforehand, and/or test your laptop with the classroom console beforehand, to avoid unexpected delays, arising due to technical difficulties, during your presentations)




Group IDs, for A1, A2, TP, listed in a FIPPA-compliant manner, i.e. anonymized




FIPPA == Freedom of Information and Protection of Privacy Act

Term Project Presentations Schedule: Monday December 02 2024 

Group 1	 5:30--5:45    N-Queens
Group 2  5:45--6:00    N-Queens
Group 3  6:00--6:15    N-Queens
Group 4  6:15--6:30    N-Queens
Group 5  6:30--6:45    Chess
Group 6  6:45--7:00    PATH PLANNING

Term Project Presentations Schedule: Wednesday December 04 2024 

Group 7  5:30--5:45    N-Queens
Group 8  5:45--6:00    SGA
Group 9  6:00--6:15    N-Queens
Group 10 6:15--6:30    N-Queens
Group 11 6:30--6:45    N-Queens
Group 12 6:45--7:00    N-Queens

Research resources

1. AAAI (Association for the Advancement of Artificial Intelligence)
2. IJCAI (International Joint Conference on Artificial Intelligence)
3. Artificial Intelligence an Elsevier journal
4. Annals of Mathematics and Artificial Intelligence a Springer journal
5. Machine Learning a Springer journal
6. Journal of Heuristics a Springer journal
7. Computational Intelligence a Wiley journal
8. LNAI (Lecture Notes in Artificial Intelligence) a Springer series
9. Canadian Artificial Intelligence Association Canadian Conference on Artificial Intelligence
10. ACM Special Interest Group on Artificial Intelligence ACM Special Interest Group on Artificial Intelligence
11. Journal of Artificial Intelligence Research

University and Course Policies (senate approved)

1. Special Needs: Students with disabilities or special needs are advised to contact Laurier’s Accessible Learning Centre for information regarding its services and resources. Students are encouraged to review the Academic Calendar for information regarding all services available on campus.
2. Plagiarism: Wilfrid Laurier University uses software that can check for plagiarism. If requested to do so by the instructor, students are required to submit their written work in electronic form and have it checked for plagiarism.
3. Academic Integrity: Laurier is committed to a culture of integrity within and beyond the classroom. This culture values trustworthiness (i.e., honesty, integrity, reliability), fairness, caring, respect, responsibility and citizenship. Together, we have a shared responsibility to uphold this culture in our academic and nonacademic behaviour. The University has a defined policy with respect to academic misconduct. As a Laurier student you are responsible for familiarizing yourself with this policy and the accompanying penalty guidelines, some of which may appear on your transcript if there is a finding of misconduct. The relevant policy can be found at Laurier's academic integrity website along with resources to educate and support you in upholding a culture of integrity. Ignorance is not a defense.
4. Classroom Use of Electronic Devices: Read WLU policy 9.3 Classroom Use of Electronic Devices.
5. Late Assignment Policy: late assignments will be marked with 0.
6. Final Examinations: Students are strongly urged not to make any commitments (i.e., vacation) during the examination period. Students are required to be available for examinations during the examination periods of all terms in which they register. Refer to the Handbook on Undergraduate Course Management for more information.
7. Foot Patrol, the Wellness Centre, Student Food Bank.