C O U R S E    O U T L I N E 



CS 462 Artificial Intelligence  

Spring Semester, 2006

2005/06 Catalog data:  Presentation of artificial intelligence as a coherent body
of ideas and methods to acquaint the student with the basic programs in the field 
and their underlying theory.  Students will explore this through problem-solving 
paradigms, logic and theorem proving, language and image understanding, search 
and control methods and learning.

Prerequisite: CS 253, or permission of instructor.

Textbooks:    Stuard Russell and Peter Norvig, Artificial Intelligence.  A Modern 
              Approach, Prentice Hall, Inc. 2002. 

Instructor:   Neli P. Zlatareva, Ph.D., Professor of Computer Science.          
Office:       MS204.            
Phone:        (860) 832-2723.            
E-mail:       zlatareva@ccsu.edu            
Web side:     http://www.cs.ccsu.edu/~neli/            
Office hours: TR  4:45 p.m. -  5:15 p.m. and 6:30 p.m. - 7:00 p.m.
              MW 11:30 a.m. - 12:30 p.m. and 1:45 p.m. - 2:45 p.m.

Course objectives:  To provide computer science students with basic knowledge on 
theory and practice of Artificial Intelligence as a discipline about intelligent 
agents capable of deciding what to do, and do it. To provide an introduction to 
Artificial Intelligence programming by exploring Common Lisp.

Topics in the course  (number of lecture hours each):

        1.  Introduction to LISP: basic LISP primitives, procedure 
definition and binding, predicates and conditionals, procedure and 
data abstraction, mapping.                                            7.0 hours

        2.  Intelligent agents: a discussion on what Artificial 
Intelligence is about and different types of AI agents.               1.0 hours

        3.  Searching as a problem-solving technique: a review of  
"conventional" searching methods including breadth-first, depth-
first, bi-directional and best-first search.  Heuristic functions 
and their effect on performance of search algorithms. Genetic
algorithms.                                                           4.0 hours

        4.  Knowledge-based agents and logical problem solving: 
introduction to knowledge representation and propositional logic.     6.0 hours

        5.  First-order logic as a basis for building intelligent
agents capable of acting and reacting in a complex environment.       6.5 hours

        6.  Knowledge engineering:  building knowledge bases and 
automated theorem provers.  Production systems as an example of 
logical problem solving.                                              5.5 hours

        7.  Uncertainty representation and management: introduction 
to truth-maintenance systems, default reasoning, and probabilistic 
problem solving.                                                      6.0 hours

        8.  Planning agents:  representation of states, goals and 
actions. The block-world example.                                     3.0 hours

        9.  Learning agents:  learning from observations and 
examples. Decision trees and the ID3 algorithm.                       3.0 hours

       10. Student presentations and class discussions.               3.0 hours

                                                     Total:          45.0 hours

Homework Assignments: There will be 4 homework assignments which will require 
Common Lisp environment. Free Common Lisp version can be downloaded from
http://www.franz.com 

Research project:  Students will explore a research topic in a common area of 
interest, write a joint paper on this research, and make a 10 to 15 minutes class
presentation.  Depending on the topic, the project can be application or 
tool-oriented involving LISP programming (in which case a 4-5 pages paper 
describing the problem and the implementation must be submitted as well as the 
code), or theory-oriented in which case a 15-20 pages paper must be submitted 
for a grade.

Tests:  There will be two tests during the semester, and a final exam.

Academic honesty: All homework and other written assignments must be an individual 
effort of the student submitting the work for grading. See the section "Policy on 
Academic Honesty" in the CCSU Student Handbook.

Grading       Homework assignments                                 5 points each
              Research paper and presentation                     10 points
              Tests                                               20 points each
              Final exam                                          30 points