CS724 Artificial Intelligence

Instructor Dr. P. Juell - http://www.cs.ndsu.nodak.edu/~juell
Office 256C IACC
Phone 231-8196
Email paul_juell@ndsu.nodak.edu
Class times: 9:30-10:45 TR 106 IACC
Office Hours 11:00-11:50pm MWF

Course schedule/outline/calendar of events 

          2001
week  Mo Tu We Th Fr 
 1 Jan    9 10 11 12 
 2     H 16 17 18 19  Martin Luther King Jr. Holiday
 3    22 23 24 25 26 
 4    29 30 31  1  2
 5 Feb 5  6  7  8  9 
 6    12 13 14 15 16
 7     F 20 21 22 23  Presidents' Day Holiday
 8    26 27 28  1  2  
 9 Mar 5  6  7  8  9 
      Spring Break   
10    19 20 21 22 23 
11    26 27 28 29 30 
12 Apr 2  3  4  5  6  
13     9 10 11 12  H  Holiday
14     H 17 18 19 20  Holiday
15    23 24 25 26 27 
16    30  1  2  3  4  
FINALS 7  8  9 10 11
Unless otherwise noted, programs will be due on Thursday(R) of stated week, tests will be on Tuesday(T) of stated week. 
week  [reading] {program- (points) due on week above)
------  AI as a paradigm - 
           take insolvable problem, microworld, bag of tricks
1     [Ch1] AI:  history and applications
      [Ch2] the predicate calculus 
      [Ch10] lisp  
2     [Ch3] structures and strategies for state space search 
            {prog1 (20) simple lisp}
      [Ch4] heuristic search  149
3     [Ch5] control and implementation of state space search 
      [Ch9] an introduction to Prolog  203
4     [Ch6] knowledge-intensive problem solving (rule-based expert systems)
      [Ch7] reasoning with uncertain or incomplete information
            {prog2 (30) blocks}
5     [Ch12] automated reasoning
            TEST 1 
6
            {prog3 (30) due T missionaries and cannibals}
            {prog4 (10) proposal for rules system due R}
7     [Ch8] knowledge representation 333
8     [Ch11] natural language  377
             {prog5 (30) full rule system }
9     [Ch8] [GUS] advanced representation in Prolog (we will use FRL in lisp)
	     {prog6 grammar for English}
10           
	     TEST 2  (R)
11    [Ch12] automated reasoning
      [Ch13] machine learning: symbolic learning
      [Ch14] machine learning: connectionist (Neural networks)
	     {prog7 (30) simple GUS}
12           genetic algorithms
13           second time around on some topics
               computational linguistics
14
             {prog8 (30) simple GA or NN program}
15
16
             TEST 3  
             {prog9 (30) grammar solving a problem}
    Final (200)

CS724 AI


EXPECTED BACKGROUND FOR COURSE Ability to deal with formal symbolic notations such as FOPC and mathematics. Skill in programming and reading programs in more than one programming language. Background in data structures and formal notations for describing programs, such as BNF grammars.

GOALS

The student will: develop an understanding of the philosophy of AI and of several AI techniques, will be able to use the techniques and could evaluate the appropriateness of using the techniques for a real problem.

OBJECTIVES

The student will: be able to solve problems using the AI techniques and the overall AI philosophy, will be able to develop programs in LISP, PROLOG and other AI programming notations, will be able to present a case, in English, for using various AI techniques.

MATERIAL

Readings in addition to the book will be required. The material will be on reserve in the library under JUELL CS724. Occasionally notices will be posted to the class home page. You are responsible for checking this information twice a week.

Problem statements, old tests and notes can be found on the WEB under the class home page. Some of the tools we will use are in ~juell/cs724pub/tools on the classroom machine (abacus) and on the SOD cluster.

Course description


Surveys major areas of AI including theorem proving, heuristic search, problem-solving, computer analysis of scenes, robotics, natural language understanding, and knowledge-based systems. Prereq. CS 372 or Graduate standing.

Evaluation procedures and criteria 

GRADING 
300 points tests (3 at 100 each) 
240 points programs
200 points final 
           (takehome: see the class home page)
 50 points miscellaneous (seldom used)
Grade calculated by summing the points received and dividing by the points attempted. Normally grades are based on 90+% A, 80+% B, 70+% C, 60+% D and 59-% F. This may be adjusted some.

PROGRAMS DUE IN CLASS, AT THE START OF CLASS, ON DATE DUE. NO CREDIT FOR LATE PROGRAMS. There are no makeup tests.

Required student resources


The book Artificial Intelligence [Luger & Stubbledfied 98]
and accounts on SOD and Abacus. You need to get the SOD account by on-line registration

Special Needs

Any students with disabilities or other special needs, who need special accommodations in this course are invited to share these concerns or requests with the instructor as soon as possible.

Academic Honesty statement

All work in this course must be completed in a manner consistent with NDSU University Senate Policy, Section 335: Code of Academic Responsibility and Conduct ( http://www.ndsu.nodak.edu/policy/335.htm).
All work is to be independent, this includes the tests, programs and the final take home test. Copying even a sentence from another student, current or previous is plagiarism. The instructor has a complete set of previous finals and views plagiarism on the final as a very serous offense.