Spring 2006

Artificial Intelligence

COSC 40503

 

Knowledge is experience,  the rest is information
                               Albert Einstein

 

Monday, Wednesday &  Friday    TTC 137   11:00-11:50 pm

 

 

Instructor:                       Antonio Sanchez       

Office:                     TTC – 332

Email:                      a.sanchez-aguilar@tcu.edu   

URL:          www.cs.tcu.edu/people/professors/asanchez/asanchez.html

Office Hours:         Monday to Friday 9:30-11:00, 12:00-13:00  & by Appointment

Final Exam                Wed may 10     11:30 – 2:00

Required Materials:                Web page located at:

             http://www.cs.tcu.edu/people/professors/asanchez/asanchez.html

 

Course Description

In this course we review and work with fundamental paradigms and methodologies of AI, past and present

 

 

 

Course Objectives

 

1.      To understand and apply the various paradigms of AI

2.      To recognize the benefits and limitations of each in the generation and process of artificial cognition

3.      To program a game using three methodologies and test them between each other

4.      To provide both information and knowledge about the history of AI

 

Course Textbook

Author: Ben Coppin

Title: Artificial Intelligence Illuminated

Jones & Barlett  Ed  2004

 

For the CLS part the following two website will be useful:

 

website 1:  http://www.lania.mx/~asanchez/tesis/index.html

website 2:  http://www.projectalisa.org/

 

 

COSC - 40503 - 030   AI        Weekly Schedule      Spring 2006

Week

Date

Lec #

Lecture Topic

Homework & Readings

 

#1

Wed - Jan 18

1

What is AI

Chapter 1

 

Frid  - Jan 20

2

A bit of AI history

 

 

#2

Mon - Jan 23

3

AI Paradigms

Chapter 2

 

Wed - Jan 25

4

Learning by adaptation

Game Selection

 

Frid  - Jan 27

5

Learning Automata

Website 1: Chapter 3

 

#3

Mon - Jan 30

6

CLS for games

 

 

Wed - Feb 01

7

Learning

Chapter 10

 

Frid  - Feb 03

8

ALISA as a CLS engine

Website 2

 

#4

Mon - Feb 06

9

Vision and Image processing

Game Update

 

Wed - Feb 08

10

Image transformation

 

 

Frid  - Feb 10

11

Industrial Applications

 

 

#5

Mon - Feb 13

12

Neural Networks

Chapter 11

 

Wed - Feb 15

13

Connectionism & Bayes

Game Follow up

 

Frid  - Feb 17

14

EXAM 1

 

 

#6

Mon - Feb 20

15

Perception

 

 

Wed - Feb 22

16

Knowledge Representation

Chapter 3

 

Frid  - Feb 24

17

Project Presentation 1

 

 

#7

Mon - Feb 27

18

Competition and cooperation

Chapter 6

 

Wed - Mar 01

19

Heuristic Functions

 

 

Frid  - Mar 03

20

Minimax

 

 

#8

Mon - Mar 06

21

Alpha Beta Prunning

Game Update

 

Wed - Mar 08

22

Depth and Breath searches

Chapter 4

 

Frid  - Mar 10

23

Advanced Search

Chapter 5

 

#9

Mon - Mar 20

24

Logic and Inference

Chapter 7

 

Wed - Mar 22

25

Rules and chaining

Chapter 8

 

Frid  - Mar 24

26

Knowledge Modeling

 

 

#10

Mon - Mar 27

27

Planning

Game Follow up

 

Wed - Mar 29

28

Expert System rules

Chapter 9

 

Frid  - Mar 31

29

EXAM 2

 

 

#11

Mon - Apr 03

30

Natural language

 

 

 

Wed - Apr 05

31

Semantic Networks, Eliza

Chapter 20

 

Frid  - Apr 07

32

Shrudlu

 

 

#12

Mon - Apr 10

33

CD and Scripts

 

 

Wed - Apr 12

34

Projects Presentation 2

 

 

#13

Mon - Apr 17

35

Genetic Algorithms

 

 

Wed - Apr 19

36

Genetic Algorithms

Chapter 14

 

Frid  - Apr 21

37

GA for Game playing

 

 

#14

Mon - Apr 24

38

Function definition

 

 

Wed - Apr 26

39

The range of AI

Game Update

 

Frid  - Apr 28

40

AI and its relations

 

 

#15

Mon - May 01

41

AI and its future

 

 

Wed - May 03

42

Projects Presentation 3

 

 

Final

 

 

 

 

 

Wed - May 10

11:30 - 2:00

 

 

 

**This schedule represents my current plans and objectives.  As we go through the semester, those plans may need to change to enhance the class learning opportunity.  Such changes, communicated clearly, are not unusual and should be expected.

 

 

 

Course Requirements (Grading)

 

 

Each

Policy

Total

3 Projects

20

Incremental presentations will be scheduled

60

2 partial exams

10

 

20

Final

10

 

20

 

 

Total

100

 

 

Course Policies:

Attendance Policy – The university attendance policy states that regular and punctual class attendance is essential and that no assigned work is excused because of absence, no matter what the cause.

Statement on Disability Services at TCU: Texas Christian University complies with the Americans with Disabilities Act and Section 504 of the Rehabilitation Act of 1973 regarding students with disabilities.  Eligible students seeking accommodations should contact the Coordinator for Students with Disabilities in the Center for Academic Services located in Sadler Hall, 11.  Accommodations are not retroactive, therefore, students should contact the Coordinator as soon as possible in the term for which they are seeking accommodations. Further information can be obtained from the Center for Academic Services, TCU Box 297710, Fort Worth, TX 76129, or at (817) 257-7486.

Academic Misconduct (Sec. 3.4 from the Student Handbook) – Any act that violates the academic integrity of the institution is considered academic misconduct. The procedures used to resolve suspected acts of academic misconduct are available in the offices of Academic Deans and the Office of Campus Life.  Specific examples include, but are not limited to:

á          Collusion: The unauthorized collaboration with another in preparing work offered for credit.

 

Netiquette: Communication Courtesy Code.  All members of the class are expected to follow rules of common courtesy in all email messages, threaded discussions and chats.  If I deem any of them to be inappropriate or offensive, I will forward the message to the Chair of the department and the online administrators and appropriate action will be taken, not excluding expulsion from the course.

 

Email Notification: The official TCU student email address will be used for all course notification. It is your responsibility to check your TCU email on a regular basis.