Introduction to Artificial Intelligence
CS 4300, Fall 2009, MW 6:55pm-8:10pm, 312 Clark Hall

Instructor
Martin Pelikan
E-mail: pelikan@cs.umsl.edu
WWW: http://www.cs.umsl.edu/~pelikan/
Note: Do not call me, I do not respond to phone messages.

Office hours
CCB 320, MW 3:30pm-­5:00pm
or by appointment (send email to arrange)

Prerequisities
CS 2260, CS 2750 and CS 3130

Textbook
Russel & Norvig, Artificial Intelligence: A Modern Approach, 2^nd edition, Prentice Hall.

Grading

• Homeworks and machine problem sets: 55%
  
• Three tests (in class, no final): 45% (15% + 15% + 15%)

Machine problem sets (MPs)
C, C++, or Java must be used for programming assignments. The code you submit must compile and run on UMSL server admiral.umsl.edu (any code that cannot be run on this server without any tweaks may score simply 0). Make sure you have access to admiral and for any problems, contact Technology Support Center (314-516-6034, or helpdesk@umsl.edu). About half of the assignments might be machine problems.

Syllabus

1. Search
   
2. Planning and action
   
3. Uncertainty and probability
   
4. Markov and decision models
   
5. Machine learning
   
6. Evolutionary computation
   
7. Reinforcement learning
   
8. Natural language processing
   
9. Planning and action
   

Additional info

• If you don't have all the prerequisities, you MUST contact me ASAP.
• Covered topics might evolve over the course of the semester based on progress and interest.
• Visit the course's web page on mygateway regularly.
• Extensions for homeworks only with prior consent of the instructor and only under extraordinary circumstances (at instructor's discretion).
• Grades will be curved at the discretion of the instructor.
• No delayed grade will be given unless really special circumstances are proven.
• Maintaining confidentiality of student grades policy: Click here.
• Student conduct code including the campus policy on academic dishonesty: Click here.
• Cancellation of student registration policy: Click here.
• Wait list policy: Click here.
• Students who require extended time or other special accomodations for exams due to disabilities must inform me about the situation in the first two weeks of the class. Then, they are responsible for arranging the requested accomodations for each exam with Disability Access Services at UMSL by one week before the exam (I must approve any changes, so start the process well ahead).
• Discussion in class is strongly encouraged.

Short bio of the instructor:
Martin Pelikan received Ph.D. from the Dept. of Computer Science at the University of Illinois at Urbana-Champaign in 2002. He joined the Dept. of Math and Computer Science at the University of Missouri at St. Louis in August, 2003. Currently, he is an associate professor of computer science. Pelikan's research focuses on genetic and evolutionary computation. He worked at the Slovak University of Technology at Bratislava, the German National Center for Information Technology at Sankt Augustin, the Illinois Genetic Algorithms Laboratory (IlliGAL) at the University of Illinois at Urbana-Champaign, and the Swiss Federal Institute of Technology (ETH) at Zurich. Pelikan's most important contributions to genetic and evolutionary computation are the Bayesian optimization algorithm (BOA), the hierarchical BOA (hBOA), and the scalability theory for BOA and hBOA. BOA and hBOA combine machine learning with genetic and evolutionary algorithms to create optimizers that can solve broad classes of optimization problems in a robust and scalable manner with few or no parameters. BOA and hBOA are among the most advanced and powerful genetic and evolutionary algorithms.