SYLLABUS
ARTIFICIAL INTELLIGENCE (AI)
CPSC  360
Fall,  2003



Overview

This course in artificial intelligence has several objectives , but the central theme is to provide you with a broad overview of the field of artificial intelligence, including expert systems, neural networks, fuzzy logic, and elements of artificial life, such as genetic algorithms.  The instructor for the course has arranged a number of resources , which include computer systems, languages, and application programs, as well as a textConsultation with the instructor is available.  The grading will be based on both computer based assignments and examinations.  The schedule for the semester contains 10 assignment/quiz combinations, a term project, and a final exam.


Objectives


Instructor

    Professor Ralph G. Hollingsworth , 225 Science Center, 826-8307
          web address:  http://muskingum.edu/~ralph/
          e-mail address:  ralph@muskingum.edu

Office Hours
 

Mondays 2:30-4 p.m.
Tuesday 9-11 a.m., 2:30-4 p.m.
Wednesday 2:30-4 p.m.
Friday 2:30-4 p.m.

Course Resources

Textbook:   Artificial Intelligence:  A Modern Approach
      by Stuart J. Russell and Peter Norvig (Prentice Hall, 2003)

Computer Systems Used:  Windows XP/Linux(a number of special application programs will be run on these systems)
Languages:  Python for most assignments; examples using Java, Scheme, and Prolog will also be explored.


Grading

Your final grade will be determined based on the components below:

Grade ranges:

Exercises will be handed-in as indicated on the following schedule.  The exercises are due at the beginning of class on Fridays, and you are required to complete the out-of-class work using your own efforts, as described when each exercise is assigned. On each Friday, we will also have a short quiz, and your score will be a combination of a grade for the exercise and a grade for the quiz.

Assignments or exams missed due to illness, extracurricular events,etc. can only be credited, submitted or taken after providing the instructor with written and signed notes from physicians, coaches, etc.  In the case of absences as a result of college events, you must give the instructor the note at least one week prior to the event.



Schedule
 

Week Of ...

Topics

Readings

Quiz/Exercise

August 25

Introduction, Intelligent Agents

1 & 2


September 1

Search Agents
3

1

September 8

Informed Search, Genetic Algorithms, Online Search agents
4

2

September 15

Constraint Satisfaction
5

3

September 22

Games and Adversaries

6

4

 September 29

Logical Agents and Inference

7 & 9

5

 October 6

Knowledge Representation

10

6

October 13-14

Fall Break, no classes


October 15

Introduction to Planning, Final Project Assigned

11

October 20

Real World Planning, Multiple Agents

12

7

October 27

KUncertainty, Bayesian Reasoning, Fuzzy Logic

13 & 14

8

November 3

Probabilistic Reasoning and Time

15

9

November 10

Learning with Observations

18

10

November 17

Learning in Baysian and Neural Networks

20

November 24

Communication and Translation
 22 & 23

 November 26-30

Thanksgiving Break, no classes

 

December 1

Robotics

25

Final Project

 December 9

Final Exam, 8:30 a.m., BSC 305