Plan for this class Welcome to 4003-380 Logistics Introduction to - - PDF document

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Plan for this class Welcome to 4003-380 Logistics Introduction to - - PDF document

Plan for this class Welcome to 4003-380 Logistics Introduction to CS Theory Syllabus & Ground Rules Student Info Forms / Attendance Joe Geigel What is this Course About ------ break --------- Discrete Math Review


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Welcome to 4003-380 Introduction to CS Theory

Joe Geigel

Plan for this class

 Logistics

 Syllabus & Ground Rules  Student Info Forms / Attendance

 What is this Course About  ------ break ---------  Discrete Math Review

Logistics

 First things first.

 Class Web site

 http://www.cs.rit.edu/~jmg/cs380  Syllabus (e-version of handout)  Schedule  Homework Assignments  Diary (including these slides)

Logistics

 mycourses

 dropboxes  RIT e-mail address forwarding  Grade book

Logistics

 Required Textbook

 An Introduction to

Formal Language and Automata, 4th Edition by Peter Linz.

 2006 Printing

Logistics

 Optional Textbook

 JFLAP: An Interactive

Formal Languages and Automata Package by Susan Rodger

 Software on

mycourses or obtain from

 www.jflap.org

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Logistics

 Prerequisite:

 1016-265: Discrete Math  1016-705: Discrete Math II

 These are important as the material in

this class is mathematical in nature.

Logistics

 About Me

 Joe Geigel  Office: 70-3527  Office Hours: MW 2-4 (and by appt)  http://www.cs.rit.edu/~jmg

Logistics

 Grading:

 Three basic course activities:

 Homework 45%  Exams (2) 30%  Final Exam 25%

Logistics

 Homework

 Homework will be assigned weekly.  Will have 1 week to complete each assn.  Due dates are definite!

 no late homeworks!  Listed in HOMEWORK section of Web site

 Group submission (max 2 people) ok  Each assignment carries equal weight  Lowest homework grade is dropped.  Some homework will require JFLAP

Logistics

 Discrete Math Quiz

 Quick quiz on basic discrete math concepts

 Proofs  Sets  Relations

 Will be given next class  Counts as an extra homework

Logistics

 Homework

 Homework problem session

 2nd half of class on days when homework is not

assigned.

 Questions about current homework

assignment.

 Similar problems done on the board.

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SLIDE 3

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Logistics

 Tutoring Center

 Dedicated Theory Tutoring  CS theory tutoring center (70-3660).  Current schedule:

 TBA

 One rule about tutors: You are not allowed to

discuss open homework problems with them.

 http://www.cs.rit.edu/~eh/tutoring.html

Logistics

 Exams

 Dates

 Thursday, October 2 (Chapters 2-4)  Thursday, October 23 (Chapters 5-8)

 Closed book…1 page study guide  No make up exams

Logistics

 Final Exam

 Given during exam week

 Exact date and time TBD

 Cumulative…sort of  Closed book…1 page study guide  Review Session: last class  No make up exams.

 Any questions so far?

Logistics

 Schedule

 Posted on SCHEDULE section of Web site  Subject to change, but indicates the best guess as

to what will be covered when

 Includes links to these slides (in PDF)  Slides should be available 1 day before the

lecture.

Logistics

 CS Dept Policy of Academic Dishonesty

 Included in hardcopy syllabus  Please read and understand.

 Speaking of student info forms

 Any questions before I hand them out?

So what is this course all about?

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Think back to 1937…

There were NO programmable computers The Golden Gate Bridge was completed Jesse Owens was celebrating his Olympic gold medal Swing was king!

Meanwhile…in Princeton, NJ

 Researchers were contemplating the following

question:

 “Can there exist, at least in principle, a definite method

by which all mathematical problems can be decided”

 In other words…a programmable computer.

 They did not have the technology…yet

 But they did have mathematics

 Mathematical models of computing

machinery!

Things you will learn

 Three basic concepts:

 Languages  Grammars  Automata

Languages

 Wikipedia says:

 A language is a system of signals, such as

voice sounds, gestures or written symbols that encode or decode information.

 For our purposes

 A language is a set of strings.

Grammars

 Wikipedia says:

 languages can be described as a system of

symbols and the grammars (rules) by which the symbols are manipulated

 Grammar is the study of rules governing

the use of language.

Grammars

 Think back to your days of learning English

 Rules for constructing a simple sentence

 Sentence = noun phrase + verb phrase  Noun phrase =  Name (Joe)  Article + noun (the car)  Verb Phrase =  Verb (runs)  Verb + prepositional phrase  Prepositional Phrase =  Preposition + noun phrase (from the car)
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Grammars

 Look at the sentence. Is this grammatically correct?

 Joe runs from the car.  Sentence = noun phrase + verb phrase  = noun + verb phrase  = Name + verb phrase  = Joe + verb phrase  = Joe + verb + prepositional phrase  = Joe + verb + preposition + noun phrase  = Joe + verb + from + noun phrase  = Joe + verb + from + article +noun

Grammars

 Look at the sentence. Is this

grammatically correct?

 Joe runs from the car.

 Sentence = Joe + verb + from + article +noun  = Joe + verb + from + the + car  = Joe + ran + from + the + car

 Valid sentence!

Automata

 Wikipedia says:

 An automaton (plural: automata) is a self-

  • perating machine.

 For our purposes:

 These machines are mathematically

defined.

Example: Tic Tac Toe

x x

  • x
  • x

x

This is a mathematical model for a machine that plays tic-tac- toe

What you will learn

 Three basic concepts:

 Languages  Grammars  Automata

 How does this help our friends from NJ?

Example: Tic Tac Toe

… …

a b c d e f g h i A B C D E F G H I a b c d e f g h i A B C D F G H I x e x

  • eI

x

  • x

x

  • eIbAh
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Languages: String Recognition problem

 Given a string and a definition of a

language (set of strings), is the string a member of the language?

Language recognition machine Input string YES, string is in Language NO, string is not in Language Different classes of machines can recognize different classes of languages

Languages

 Take home message:

 Languages and problems are the same

thing

 Encode problems to create strings  Add semantics to strings that represent

problems.

 Consider encoding with 0’s and 1’s…hmmm

Languages and grammars

 Furthermore…

 We can define grammars that describe

given languages.

Languages

 Will actually be looking at classes of

languages:

 Each class will have its own class of

grammars.

 Each class will have its own machine model

for string recognition

 Languages and machines get more

complex as we move forward in the course.

Languages

 Practical Uses of String Recognition

 Syntax of Computer languages are defined by

grammars

 Parsing / Compilers / Interpreters  These mathematical models are used to parse

programs written in modern computer languages

 Questions so far?

Computation: One step further

 Computation

 Basic questions in computer science

 Computability: What problems can and cannot be

computed?

 Complexity: If a problem can be solved using a

“computing machine”, how long will it take ?

 Approach

 All this theory was developed before the advent of

computers!

 Develop a mathematical model for a “computer”  “Run” your problem using this model to test for

computability and efficiency

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So in short…

Theory of Computation Computation

Computability Complexity

Languages

Parsers / compilers / grep / programming languages, etc

But all this is to come….

 We’ll start with the basics…

 after the break

 Any questions?