1 welcome to cpts 317 background course outline textbook syllabus (see class web site to important...
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Welcome to CptS 317Background
Course OutlineTextbookSyllabus
(see class web site to important information on disabilities, cheating
and safety)Grades
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Nuts and Bolts
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CptS 317Automata Theory, Languages and
ComputationFall 2014
Instructor: John Miller, West [email protected]
Class web page can be found athttp://www/tricity.wsu.edu/~jhmiller
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Background
In 1930s A.Turing studied abstract machines (Turing machine) with properties like modern computers.
His objective was to discover what computers could and could not do.
This subject now called “deciability” If problem can be solved by
computer, it is “decidable”
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Background (2) In 40s and 50s, simple machines
called “finite automata” were studied as models of brain function.
Although not good brain models, they turned out to be useful for other reasons.
In 1950s, N. Chomsky introduced the concept of “grammars” that is closely related to finite automata.
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Background (3)
In 1969 S. Cook extended Turing work. He devised ways to separate computer
problems into those that could be solved efficiently (tractable) from those that took so much time that computers are useless (intractable or NP-hard).
CptS 317 is about these classical issues in the theory of computing.
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Course Outline
Regular Languages and their descriptors: Finite automata, nondeterministic
finite automata, regular expressions. Algorithms to decide questions about
regular languages, e.g., is it empty? Closure properties of regular
languages.
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Course Outline – (2)
Context-free languages and their descriptors: Context-free grammars, pushdown
automata. Decision and closure properties.
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Course Outline – (3)
Recursive and recursively enumerable languages. Turing machines, decidability of
problems. The limit of what can be computed.
Intractable problems. Problems that (appear to) require
exponential time. NP-completeness and beyond.
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Text
Introduction to Automata Theory, Languages, and Computation 3rd Edition, Hopcroft, Motwani, Ullman,
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Likely course content
Chapter 1: IntroductionChapter 2: Finite AutomataChapter 3: Regular Expressions and LanguagesChapter 4: Properties of Regular LanguagesMidterm examChapter 5: Context-Free Grammars and LanguagesChapter 6: Pushdown AutomataChapter 7: Properties of Context-Free LanguagesChapter 8: Introduction to Turing MachinesFinal exam
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Grades
Homework 25% Weekly quizzes 25%: Midterm exam 25% Final exam 25%
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Comments About Homework The intent is that everyone will get
homework 100% correct. You are allowed to try as many
times as you like. Only the last try counts.
Don’t be afraid to guess and try again.
You’ll get some advice if you make a mistake.
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Quizzes: when and why
End of class on Fridays Questions about the material covered in
during that week Open textbook and lecture slides
Reward students who come to class, read text and review lecture slides
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Why Study Automata?
Finite automata are models for protocols, electronic circuits, etc.
Regular expressions are essential for all types of computing
Context-free grammars are used to describe the syntax of almost every programming language.
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Why? – (2) When developing solutions to real
problems, we often confront the limitations of what software can do. Undecidable things no program can
do Intractable things programs can do
but but no fast programs exist.
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Practical Application
“Intractable” problems should not be addressed “head on” (i.e. write code based on rigorous step-by-step method)
Look for an approximate method Try “heuristic” approach (likely to
give the correct answer by no guarantee)
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Gradiance Problems The “class token” is 8E58F2FF. Register it at www.gradiance.com/service See Texts p35 for discussion and 1st set of
problems Pearson no longer supports Gradiance Jeffery Ullman offers service free of charge Find Ullman’s online course at
infolab.stanford.edu/~ullman/ialc.html My lecture slides were developed from his