CP468 ARTIFICIAL INTELLIGENCE, WINTER 2013, WLU

Course Description

Prerequisites

Instructor

Important Course Information

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. Research Projects Presentations

Class Schedule, Winter Semester Timetable

            |     Tue     |     Thu     |   
            | 13:00-14:20 | 13:00-14:20 | 
            | Room N1058  | Room N1058  | 
____________|_____________|_____________|______
            |             |             |
Week 1:     |  Jan 08     |    Jan 10   |   
Week 2:     |  Jan 15     |    Jan 17   |   
Week 3:     |  Jan 22     |    Jan 24   |   
Week 4:     |  Jan 29     |    Jan 31   |   
Week 5:     |  Feb 05     |    Feb 07   |   
Week 6:     |  Feb 12     |    Feb 14   |   
____________|_____________|_____________|______________

Reading Week   Feb 18 - Feb 22   N o  C o u r s e s
_______________________________________________________
            |             |             |
Week 7:     |  Feb 26     |   Feb 28    |   
Week 8:     |  Mar 05     |   Mar 07    |   
Week 9:     |  Mar 12     |   Mar 14    |   
Week 10:    |  Mar 19     |   Mar 21    |  
Week 11:    |  Mar 26     |   Mar 28    |  
Week 12:    |  Apr 02     |   Apr 04    |   
____________|_____________|_____________|______________
            |             |             |

Course Mailing List

Course Requirements/Student Evaluation

• The course final grade is computed based on the 5 components: A1, A2, M, TP, RAP, explained in more detail below.

• The course final grade is computed as: A1*(15/100) + A2*(15/100) + M*(30/100) + TP*(30/100) + RAP*(10/100)

• (A1) Assignment 1: 15%, due date: Thursday, January 31, 2013.

• (A2) Assignment 2: 15%, due date: Thursday, February 28, 2013.

• Important Information regarding assignment submission:
  • All assignment submissions will be by e-mail only.

  • All assignment submissions will be acknowledged by e-mail.

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

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

  • Send one .pdf file only, for the entire assignment.

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

  • Do not use a cover page. Instead, make sure that all pages of your .pdf file are numbered and on each page include a header with your name, course code, date, and A1 (or A2)

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

• (M) Midterm: 30%, Thursday, February 28, 2013, in class.

• (TP) Term Project: 30%, due date: Thursday, April 4, 2013.

  All students will be required to prepare a Term Project, details in class. Students may form groups (of no more than 3 students each) to work on the Term Project collaboratively. Each group will have to deliver a project document and arrange for a project demonstration.

• (RAP) Research Article Presentation: 10%, Week 12 of classes.

  Each student is required to study, understand and present a research article (published in a research journal or a research conference) relevant to AI research. Half-hour presentations (20-min talk + questions/answers) will be scheduled for the last week of courses. Students are required to work on this project individually.
  Some sources of finding such research papers are: (on-line access also from Trellis)

  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. Journal of Artificial Intelligence Research