CP468 ARTIFICIAL INTELLIGENCE, FALL 2016, WLU

Course Description

Prerequisites

Instructor

Important Course Information

Course Textbook

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

A1

date posted: September 22, 2016
due date: October 6, 2016

A2

date posted: October 26, 2016
due date: November 9, 2016
code demo: November 10, 2016

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, Fall Semester Timetable

              |     Mon     |     Wed     |
              | 17:30-18:50 | 17:30-18:50 |
              |    N1057    |    N1057    |
______________|_____________|_____________|_
              |             |             |
Week 1:       |  Sep 12     |   Sep 14    |
Week 2:       |  Sep 19     |   Sep 21    |
Week 3:       |  Sep 26     |   Sep 28    |
Week 4:       |  Oct 03     |   Oct 05    |
---------------------------------------------
Oct 10, Thanksgiving, Oct 11 - 14 Fall Reading Week
---------------------------------------------
Week 5:       |  Oct 17     |   Oct 19    |
Week 6:       |  Oct 24     |   Oct 26    |
Week 7:       |  Oct 31     | Nov 02 (M)  |
Week 8:       |  Nov 07     |   Nov 09    |
Week 9:       |  Nov 14     |   Nov 16    |
Week 10:      |  Nov 21     |   Nov 23    |
Week 11:      |  Nov 28     |   Nov 30    |
Week 12:      |  Dec 05     |   Dec 07    |
______________|_____________|_____________|__
              |             |             |

Course Requirements/Student Evaluation

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

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

• (A1) Assignment 1: 20%, due date: TBA.

• (A2) Assignment 2: 20%, due date: TBA.

• Important Information regarding assignment submission:
  • Late assignments will be marked with 0.
  • 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)

  • Your .pdf file should have a cover page, all pages should be numbered and on each page include a header with your name, course code, submission date, and A1 (or A2)

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

• (M) Midterm: 30%, November 02, 2016, in class.

• (TP) Term Project: 30%, due date: December 4, 2016

  All students will be required to prepare a Term Project, details in class. Students may form groups (of no more than 4 students each) to work on the Term Project collaboratively. Each group will have to deliver a project document and conduct a project demonstration.

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)

Monday, December 5, 2016:

Group 1:  5:30 -- 5:45 	PathPl LG MA JC BO

Group 2:  5:45 -- 6:00 	NN-based Intrusion Detection System RM DR

Group 3:  6:00 -- 6:15 	PathPl AC LH PM

Group 4:  6:15 -- 6:30 	CSP N-Queens UM

Group 5:  6:30 -- 6:45  PathPl PP OF CS

Group 6:  6:45 -- 7:00 	PathPl AR BK GN WY

Group 7:  7:00 -- 7:15 	CSP N-Queens SZ XG YL 

Wednesday, December 7, 2016:

Group 8:  5:30 -- 5:45   CW(n,k) LC JS WW

Group 9:  5:45 -- 6:00   CSP N-Queens TT RA KM BW

Group 10:  6:00 -- 6:15  GAs CG

Group 11:  6:15 -- 6:30  GAs JL SG RH

Group 12:  6:30 -- 6:45  CW(n,k) QO MO

Group 13:  6:45 -- 7:00  PathPl NH JS XG

Resources for further study

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