Math 365 

Automata Theory 

Spring 2020 

11-11:50 MTR 

UPDATED 3.17.20


Dr. Don Thompson 


Reading Material: 

Selected Research Papers & Tutorials 

            Required Textbook:  Introduction to the Theory of Computation, 3rd

Edition, Michael Sipser, Cengage Learning, ISBN: 113318779X  


Office Hours:  M 10, T 15, R 15 


Attendance Policy: 

Attendance will be taken every day.  Each student is permitted two excused absences, following which their course average will be decremented 1% per absence 


Course Description & Goals: 

This is a mathematics course designed to explore the boundaries of  knowledge in terms of information, computability and artificial intelligence.  Students are expected to gain mastery level understanding of:  Turing Machines, Finite State Automata, Computational Complexity, Classic Unsolved Computing Problems, Neural Networks, & Bayesian Networks.  


Group Participation: 

I will randomly divide the class into groups of 2 or 3.  For all group work, the entire group will be given the same grade tempered by the intra group member grade that is anonymously provided by each



Exam Schedule (Individual): 

Open Book Midterm February 27 (25%) 

Take Home Final Exam April 30 (25%) 


Group Homework:  

Assigned each Thursday, due the following Thursday (5%) 


Research Papers:  

Every Thursday I will distribute a research paper or tutorial to be discussed the following Thursday.  Research Paper Executive Summaries (2-3 pp.) from each group are then due the following 

Thursday (15%) 


Group Project Presentations:  

Each student will present a 20 minute summary of a contemporary topic in AI during the last week of class (20%) 


Discussion Format: 

This class will use the pedagogy of shared inquiry. Each Monday and Tuesday, we will convene class to discuss assigned reading from the textbook and other selected readings.  No lectures.  


Class Discussion Participation: 

Each individual student’s class participation will be graded as a function of their answering and asking questions during class discussion  (10%) 


 Weekly Schedule 


January 13 

             Chapter 0 (Sipser), Chinese Room Experiment Paper,  French Scrabble 


(January 21  

           Chapter 0,  Noam Chomsky Paper)


January 27  

            Chapter 1,  Noam Chomsky Paper


February 3

            Chapter 1, Richard Hamming Paper 


February 10 

             Chapters 2,  Raisbeck Information Theory, Raisbeck Completion



February 17  

            Chapter 2, Turing Imitation Game Paper 


February 24  

            Chapter 3, Open Book Midterm


March 9  

            Chapter 3,  Godel's Incompleteness


March 16  

            Chapter 4, Turing Halting Problem Paper 



March 23  

Chapter 4, Nick Bostrom Paper,


March 30  

            Chapter 5, Stephen Cook Paper 


April 6  

            Chapter 7, Artificial Neural Networks Tutorial  


April 13 

            Chapter 7, Bayesian Neural Networks Tutorial 


April 20  

Chapter 7, AI Report - Individual, Pre-Approved Topic


April 27        

TIMED Take Home, Individual Final Exam 



The mission of Pepperdine University calls for “highest standards of academic   excellence and Christian values, academic excellence.”  This course embodies   those standards in three ways: 

     The discipline of mathematics requires the best of its students.  We deepen this commitment by reading and discussing great works at the boundary of mathematics, computer science, and human knowledge. 

     Christian values include the cardinal virtues: courage, wisdom, temperance, and justice.  This course seeks to increase student wisdom and requires that students use courage to grapple with challenging material in order to attain its mastery. 

     Finally, the pedagogy of this course requires that we learn from each other as well as from the scientific voices of the past and present.  This affirms our desire to build and maintain an academic community,

which means we wish to employ the best practices of the life of the mind.