Homepage for COSC 4350 (Spring 1998) (Dr. Eick)
Artificial Intelligence Programming

www-address: http://www.cs.uh.edu/~ceick/4350.html

News COSC 4350 Spring 1998(last updated: May 14, 98)

I expect the grades to be ready by Saturday, May 16, 5p, probably earlier. Those that signed to publish their grades will receive a grade report by e-mail. Please do not forget to turn in the requested program hardcopies by May 15.

I will be out of town for the next two weeks. If you like to discuss matters concerning the class just contact me by the end of May and we set up an appointment in June; I will be mostly in Houston in June 1998. Those I will not see soon a like to wish a happy and productive Summer 1998. I had fun teaching the class!


The final exam is scheduled for Thursday, May 14, 11a; the review sheet for the final exam can be accessed by following the indicated link! The Results of TEST1 and TEST2 are available now!

Training Data for your genetic programming system (Assignment 4) consisting of two symbolic regression problems can be found by following indicated link (each consists of 25 data points). Report the average Manhattan error of the best solution for each benchmark. Students that find the best solution will win a special prize. Legal solutions are limited to trees with at most 45 crossover points. A LISP-environment that employs genetic programming to solve a symbolic regression problem can be found in the file gp.l in the www 4350 directory! Compile your functions using compile-file, because if you do not do so your system will be very slow (it might be still slow after compiling...).

The LISP-programs found in the newest edition of our textbook are now online! Just access the following directory by following this link (the directory contains all LISP-programs of the second edition of the textbook and a few programs provided by the instructor of the class). It should be worthwhile to load, execute, understand, and analyze some of these programs in the upcoming months, especially those that are discussed in chapters 3, 5, 7 and 14 of the textbook.

If you want to get from the outside into the COSC-computer network you have telnet into hermes, and the rlogin into the machine of your desire. Do not do your work on hermes! If you want to run akcl, rlogin into one of the Sunwork-station (e.g. crane, dodo, or chicken) and just type:
akcl
If this doesn't work (because a path is missing in your .cshrc file) type:
/usr/local/bin/akcl

An interpreter for for Allegro Common Lisp that you can download and install on your PC is available on the world-wide Web. The URL is:
http://www.franz.com/
Franz Inc. is the company that sells this implementation of Common Lisp.

Assignments for COSC 4350 can be accessed by following this link(Note that this file will be updated, if the need arises! Currently, it contains all the problems for Spring 1998 with the exception of problem 11, that will be added by the end of March 1998).

An example run of the modified LEIBNIZ-system you have to develop in problem 8 can now be accessed by following the indicated link! Moreover, an example production system to test your program for problem 9 is now available.


General Course Information COSC 4350 for Spring 1997

Instructor: Dr. Christoph F. Eick
            office hours: TU noon-1 WE 3-4p  in PGH 589 
class room: 211 AH

0)     Exam Dates and Weights  
       EXAM1        Tu., March 10, 10:00a       17% 
       EXAM2        Th., April 16, 10:00a       20%     
       FINAL EXAM   Th., May 14, 11a            30% 
       COURSE PROJECTS                          33% 
1)     CANCELLED CLASSES: Th., January 29; Th., March 26
       MAKE-UP CLASS: Fr., April 24, 4:30-7:00p
2) There will be 5 homeworks/porgramming projects. Assignments and 
   programming projects are due at 7p at the day specified. This semester's due 
   dates are: Feb. 6, Feb. 23, March 12, April 6, and April 27. No late 
   assignments are accepted; that is, assignments submitted after the due date 
   will not be graded. However, each 
   student is allowed to turn in one of the five assignments 5 days late. 
   Assignments have to be submitted electronically at the due date; hard copies 
   have to be turned in during the next class following the due date. 
3) There will be ungraded homework, whose solutions will be discussed in
   class. Students are strongly advised to do this homework, which are a 
   good preparation for the exams of COSC 4350.
4) Each student has to have a weighted average of 50.0 or higher in the three 
   exams of the course in order to receive a grade of "D-" or better for the 
   course. All exams of the class are "open textbook". 
5) Only machine written reports are accepted (the only exception
   to this point are figures and complex formulas) in the assignments.
6) Do not throw away returned assignments or tests.  
7) Be aware of the fact that our only source of information is what you 
   have turned in. If we are not capable to understand your solution, you 
   will receive a low score.
8) Assignments are individual products. Copying of reports, programs or parts 
   of programs written by other students, stealing of program listings,    
   cheating at exams and other violations of the academic honesty code will be
   penalized by dropping the involved students from the course (with grade F); 
   moreover, we will try everything in our power to remove cheaters from our     
   degree program. 
9) Translation number to letter grades:
   A:100-90  A-:90-86  B+:86-82  B:82-78  B-:78-74  C+:74-70
   C: 70-66  C-:66-62  D+:62-58  D:58-54  D-:54-50  F: 50-0
10) After submission, please leave your files untouched and do not destroy them 
    until the assignment has been graded. This guarantees that no problem 
    will occur in the case that your electronic submission fails due to 
    obscure reasons.
11) Visit this 4350-www-page frequently! It will contain all important 
    news concerning the class!


                   COURSE OUTLINE COSC 4350                   
               "Artificial Intelligence Programming"

Main textbook: Stephen Tanimoto: "The Elements of Artificial Intelligence
               using Common LISP", Computer Science Press, New York,
               Second Edition(gives a brief introduction to
               LISP and centers on discussing LISP-programs that 
               solve typical problems of Artificial Intelligence).
               The following chapters will be covered in the class:
               1-2-5-3-7-14-[10]-6  []:= only partially covered

LISP book:      Paul Graham: "ANSI COMMON LISP", Prentice Hall, 1996 (gives
                a more indepth introduction to LISP, but does not cover
                too much AI; well written and very helpful for writing
                LISP prgrams, even as a manual).

Topics: 1) Introduction to the programming language LISP
        2) Development of (LISP) programs that simulate human
           intelligence
        3) Methods and techniques of Artificial Intelligence focusing on 
           the areas: a) Heuristic Search  b) Rule-based Systems, Expert 
           Systems and Knowledge-Based Systems c) Automated Theorem Proving 
           d) Symbolic Programming e) Probabilistic Reasoning f) Genetic 
           Programming 

Prerequisite: Programming experience(COSC 1410, 2320)
 
Topics (one class = 1 hour of teaching):
   I Introduction to Artificial Intelligence[2 classes]
   II LISP[12]
      1. Basic concepts of LISP[1]
      2. Representation and Transformation of list structures[2]
      3. Recursive Programming in LISP[2]
      4. Iterative Programming in LISP[1]
      5. Data Structures in LISP[1]
      6. Case Studies in Symbolic Programming [2]
      7. Macros in LISP [2]
      8. Advanced Features in LISP [1]
   III Heuristic Search[12]
      1. Characterization and Classification of (Heuristic) Search Problems[2]
      2. Basic Search Strategies(Backtracking, Hill Climbing, Graphsearch)[4]
      3. Case studies in Heuristic Search[4]
      4. A* [2]
   IV Rule Based Expert Systems[6]
      1. What is a Rule Based Expert System[1]
      2. Techniques in Expert Systems[1]
      3. Unification[1]
      4. Bayesian Inference Networks and their Application
         in Diagnostic Expert Systems [3]
   V  Genetic Programming [6]
      1. Genetic Algorithms and Genetic Programming [2]
      2. How does Genetic Programming work? [1]
      3. Case Study: 2 Example Applications of Genetic Programming [3]       
   VI Resolution and Theorem Proving[5]
      1. Introduction to Predicate Calculus[2]
      2. The Resolution Method [2]
      3. Resolution and PROLOG [1]
                                               
  Laboratory projects:
  a) Development of various small LISP-programs using different concepts of 
     the language solving problems of symbolic programming [2 weeks]
  b) Implementation of several search strategies for different heuristic
     search problems[3 weeks].         
  c) Implementation of a Bayesian Inference Network for Diagnostic
     Decision Making [2 weeks]
  d) Application of Evoluationary Programming to example problems [3 weeks] 
  e) Advanced Concepts in LISP (macros, catch&throuw,...) [2 weeks]


Remark: Topics of Lab projects might change due to change in
programming assignments.

Accesses since 12/8/96:

last updated: May 12, 1998 at 8p