welcome to cse105 and happy and fruitful new year
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Welcome to CSE105 and Happy and fruitful New Year. שנה טובה (Happy New Year). Staff. Instructor: Amos Israeli room 2-108 . Office Hours: Fri 10-12 or by arrangement Tel#: 53 4-886 e-mail: aisraeli “at” cs.ucsd.edu - PowerPoint PPT PresentationTRANSCRIPT
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Welcome to CSE105and
Happy and fruitful New Year
טובה שנה(Happy New Year)
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Staff
Instructor: Amos Israeli room 2-108 .Office Hours: Fri 10-12 or by arrangement Tel#: 534-886e-mail: aisraeli “at” cs.ucsd.edu
TA: William Matthews Office Hours: William Matthews e-mail: wgmatthews “at” cs.ucsd.edu
• Web Page:http://www.cse.ucsd.edu/classes/wi09/cse105
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Meeting Times
Lectures: Tue, Thu 2:00p - 3:20p Cognitive Science Building 001
Sections: Mon, 1:00p - 1:50p Pepper Canyon Hall 120 – Will Tue, 2:00p - 2:50p WLH 2205 – Amos
Note: Students should come to both sections.Mid-term: Thu. Feb. 12 14:00-15:20 CSB 01Final: Thu Mar 19 15:00a - 18:00p TBA
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Homework
There will be 6-7 assignments.Assignments will be given on Monday’s section
and must be returned by the Thu lecture one week later.
First assignment is already given.
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Academic Integrity
• You are encouraged to discuss the assignments problems among yourselves.
• Each student must hand in her/his own solution.
• You must Adhere to all rules of Academic Integrity of CS Dept. UCSD and others.(Meaning: no cheating or copying from any source)
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Grading
• Assignments: 20%• Midterm: 30% - 0% (students are allowed to
drop it), open book, open notes. • Final: 50% - 80%, open book, open notes.
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Grading
• A: (85-100)• B: (70-84)• C: (55-69)• D: (40-54)• F: (0-39)Students who get a c- can ask me to bump their
grade to D if they wish.
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Bibliography
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Required: Michael Sipser: Introduction to the Theory of Computation, Second Edition, Thomson.
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Introduction to Computability Theory
Lecture1: Finite Automata and Regular Languages
Prof. Amos Israeli( ישראלי' עמוס (פרופ
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Introduction
Computer Science stems from two starting points:
Mathematics: What can be computed?And what cannot be computed?Electrical Engineering: How can we build
computers?Not in this course.
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Introduction
Computability Theory deals with the profound mathematical basis for Computer Science, yet it has some interesting practical ramifications that I will try to point out sometimes.
The question we will try to answer in this course is:
“What can be computed? What Cannot be computed and where is the line between the two?”
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Computational Models
A Computational Model is a mathematical object (Defined on paper) that enables us to reason about computation and to study the properties and limitations of computing.
We will deal with Three principal computational models in increasing order of Computational Power.
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Computational Models
We will deal with three principal models of computations:
1. Finite Automaton (in short FA).recognizes Regular Languages .
2. Push Down Automaton (in short PDA).recognizes Context Free Languages .
3. Turing Machines (in short TM).recognizes Computable Languages .
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Alan Turing - A Short Detour
Dr. Alan Turing is one of the founders of Computer Science (he was an English Mathematician). Important facts:
1. “Invented” Turing machines.2. “Invented” the Turing Test.3. Broke into the German submarine transmission
encoding machine “Enigma”.4. Was arraigned for being gay and committed
suicide soon after. 14
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Finite Automata - A Short Example
• The control of a washing machine is a very simple example of a finite automaton.
• The most simple washing machine accepts quarters and operation does not start until at least 3 quarters were inserted.
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Control of a Simple Washing Machine
• Accepts quarters.• Operation starts after at least 3 quarters were
inserted.• Accepted words: 25,25,25; 25,25,25,25; …
25 25
25
0q 75q25q 50q25
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Finite Automata - A Short Example
• The second washing machine accepts 50 cents coins as well.
• Accepted words: 25,25,25; 25,50; …
25 25,50
25,50
0q 75q25q 50q25
50 50
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Finite Automata - A Short Example
• The second washing machine accepts 50 cents coins as well.
• The most complex washing machine accepts $1 coins too.
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25,50,100
0q 75q25q 50q25
50 50,100
100
25,50,100
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},,{ 10 qqqQ s
Finite Automaton - An Example
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sq
1q
0q0
1
States:
0,1
0,1
Initial State: sq
Final State: 0q
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Finite Automaton – An Example
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,
,
sq
1q
0q0
1
0,1
0,1
Accepted words: ,...001,000,01,00,0
Transition Function: 00, qqs 11, qqs
000 1,0, qqq 111 1,0, qqq
Alphabet: . 1,0 Note: Each state has all transitions .
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A finite automaton is a 5-tupple where:
1. is a finite set called the states.2. is a finite set called the alphabet.3. is the transition function.4. is the start state, and5. is the set of accept states.
Finite Automaton – Formal Definition
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,
,
FqQ ,,,, 0
Q
QQ :
Qq 0
QF
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1. Each state has a single transition for each symbol in the alphabet.
2. Every FA has a computation for every finite string over the alphabet.
Observations
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,
,
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1. accepts all words (strings) ending with 1.
The language recognized by , called
satisfies: .
1 withends |2 wwML
Examples
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2M
2M 2ML
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How to do it
1. Find some simple examples (short accepted and rejected words)
2. Think what should each state “remember” (represent).
3. Draw the states with a proper name.4. Draw transitions that preserve the states’
“memory”.5. Validate or correct.6. Write a correctness argument.
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The automaton
Correctness Argument: The FA’s states encode the last input bit and
is the only accepting state. The transition function preserves the states encoding.
1q
sq
0q
1q1
0
1
0
1 0
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1. accepts all words (strings) ending with 1.
.
2. accepts all words ending with 0.
2’. accepts all words ending with 0 and the
empty word . This is the Complement Automaton of .
Examples
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2M
1 withends |2 wwML
3M
4M
2M
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1. accepts all words (strings) ending with 1.
.
2. accepts all words ending with 0.
3. accepts all strings over alphabet
that start and end with the same symbol .
Examples
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2M
1 withends |2 wwML
3M
4M ba,
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4. accepts all words of the form
where are integers and .
5. accepts all words in .
Examples (cont)
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5M
6M 10,01,00,1,0
nm10
0, nmnm,
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4 of multiplea is value
binary whosestringsbit 3L
• Definition: A language is a set of strings over some alphabet .
• Examples:– –
–
Languages
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1110001,10,1,01 L integers positive are ,|102 mnL nm
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• A language of an FA, , , is the set of
words (strings) that accepts.
• If we say that recognizes .
• If is recognized by some finite automaton
, is a Regular Language.
Languages
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,
M ML
M
MLLa M La
La
A La
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Q1: How do you prove that a language is regular?
A1: By presenting an FA, , satisfying .
Q2: Why is it important?
A2: Recognition of a regular language requires a controller with bounded Memory.
Q3: How do you prove that a language is not regular?
A3: Hard! to be answered on Week3 of the course.
Some Questions
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M MLLa
La
La
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In this talk we:
1. Motivated the course.
2. Defined Finite Automata (Latin Pl. form of automaton).
3. Learned how to deal with construction of automata and how to come up with a correctness argument.
Wrap up
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