FINITE STATE AUTOMATA
|
|
- Alison Bradley
- 5 years ago
- Views:
Transcription
1 FINITE STATE AUTOMATA
2 States An FSA has a finite set of states A system has a limited number of configurations Examples {On, Off}, {1,2,3,4,,k} {TV channels} States can be graphically represented as follows: On Off
3 Input An FSA is defined over an alphabet The symbols of the alphabet represent the input of the system Examples {switch_on, switch_off} {incoming==0, 0<incoming<=10, incoming>10}
4 Transitions among states When an input is received, the system changes its state The passage between states is performed through transitions A transition is graphically represented by arrows: On Off
5 Simple examples (flip-flop) On T T Off S On R S Off R
6 FSA FSAs are the simplest model of computation Many useful devices can be modeled using FSAs but they have some limitations
7 Formally An FSA is a triple <Q, A, δ>, where Q is a finite set of states A is the input alphabet δ is a transition function (that can be partial), given by δ: Q A Q Remark if the function is partial, then not all the transitions from all the possible states for all the possible elements of the alphabet are defined
8 Partial vs Total Transition Function switch_on switch_off switch_off On Off switch_on An FSA with a total transition function is called complete
9 Recognizing languages In order to be able to use FSAs for recognizing languages, it is important to identify: the initial conditions of the system the final admissible states Example: The light should be off at the beginning and at the end
10 Elements The elements of the model are States Transitions Input and also Initial state(s) Final state(s)
11 Graphical representation Initial state Off Final state Off
12 Formally An FSA is a tuple <Q, A, δ, q 0, F>, where Q is a finite set of states A is the input alphabet δ is a (partial) transition function, given by δ: Q A Q q 0 Q is called initial state F Q is the set of final states
13 Move sequence A move sequence starts from an initial state and is accepting if it reaches one of the final states switch_on On switch_off Off switch_off switch_on
14 Formally Move sequence: δ : Q A Q δ is inductively defined from δ δ (q,ε) = q δ (q,yi) = δ(δ (q,y), i) Initial state: q 0 Q Final (or accepting) states: F Q x (x L δ (q 0,x) F)
15 A practical example Recognizing Pascal identifiers <letter> <letter> q 0 q 1 <digit> q E <digit> <digit> <letter>
16 FINITE STATE TRANSDUCERS
17 Automata as language translators Input tape Control device (finite state) Output tape A finite state transducer is an FSA that works on two tapes. it is a kind of ``translating machine''.
18 The idea y = τ(x) x: input string y: output τ: function from L 1 to L 2 Examples: τ 1 the occurrences of 1 are doubled (1 --> 11) τ 2 a is swapped with b (a <---> b): but also Compression of files Compiling from high level languages into object languages Translation from English to Italian
19 Informally Transitions with output q i/w q Example: τ halves the number of 0 s and doubles the number of 1 s 1/11 0/ε 1/11 q 0 q 1 0/0
20 Formally A finite state transducer (FST) is a tuple T = <Q, I, δ, q 0, F, O, η> <Q, I, δ, q 0, F>: just like acceptors O: output alphabet η : Q I O * Remark: the condition for acceptance remains the same as in acceptors The translation is performed only on accepted strings
21 Translating a string As we did for δ, we define η* inductively η * (q,ε) = ε η (q,y.i) = η (q,y).η(δ (q,y), i) Remark η*: Q I * O * x (τ(x) = η (q 0,x) iff δ (q 0,x) F)
22 PUMPING LEMMA
23 Cycles There is a cycle: q1 ----aabab---> q1 b a b q0 q1 q2 q9 b b a a q5 a q4 q3 b q8 a b q6 q7 If one goes through the cycle once, then one can also go through it 2,3,, n times
24 More formally If x L and x Q, then there exists a q Q and a w I + such that: x = ywz δ (q,w) = q Therefore the following also holds: n 0 yw n z L This is the Pumping Lemma (one can pump w)
25 Consequences of pumping lemma L =? L =? x L y L y < Q : Just remove all cycles from the FSA accepting x Check by a similar argument whether x L Q <= x < 2 Q Note that in general knowing how to answer the question x L? for a generic x, does not entail knowing how to answer the other questions It works for FSAs, but
26 Impact in practice Are we interested in a programming language consisting of 0 correct programs? Are we interested in a programming language in which one can only write a finite number of programs?...
27 A negative consequence of pumping lemma Is the language L = {a n b n n > 0} recognized by some FSA? Let us suppose it is. Then: Consider x = a m b m, m > Q and let us apply P.L. Possible cases: x = ywz, w = a k, k > 0 ====> a m + r k b m L, r : NO x = ywz, w = b k, k > 0 ====> same x = ywz, w = a k b s, k, s > 0 ====> a m-k a k b s a k b s b m-s L: NO
28 Intuitively In order to count an arbitrary n we need an infinite memory! Rigorously speaking, every computer is an FSA, but it is the wrong abstraction: intractable number of states! (same thing as studying every single molecule in the flight of an airplane) Importance of an abstract notion of infinity From the toy example {a n b n } to more concrete cases: Checking well-balancing of brackets (typically used in programming languages) cannot be done with finite memory We therefore need more powerful models
29 OPERATIONS ON FSA
30 Closure in math A set S is closed w.r.t. an operation OP if, when operation OP is applied to elements of S, the result is still an element of S Examples: Natural numbers are closed w.r.t. sum (but not subtraction) Integers are closed w.r.t. sum, subtraction, multiplication (but not division) Rationals Reals
31 Closure for languages L = {L i }: family of languages L is closed w.r.t. operation OP if and only if, for every L 1, L 2 L, L 1 OP L 2 L. R: regular languages (recognized by FSAs) R is closed w.r.t. set-theoretic operations, concatenation, *,
32 Intersection A The parallel run of A and B can be simulated by coupling them b a a q 0 q 1 q 2 q 9 B p 0 b a a p 1 p 2 p 9 p a a <A,B> q b 0 0 q 1 p 1 q 2 p 2 q 9 p 9
33 Example A 1 : a A 2 : a q 0 q 1 p 0 a a q 0 p 0 q 1 p 0 a 33
34 Formally Given A 1 = <Q 1, I, δ 1, q 01, F 1 > A 2 = <Q 2, I, δ 2, q 02, F 2 > < A 1, A 2 > = <Q 1 Q 2,I,δ,<q 01,q 02 >,F 1 F 2 > δ(<q 1,q 2 >, i) = <δ 1 (q 1, i), δ 2 (q 2,i)> One can show (by simple induction) that L(< A 1,A 2 >) = L(A 1 ) L( A 2 ) Can we do the same for union?
35 Union The union is built analogously Given A 1 = <Q 1, I, δ 1, q 01, F 1 > A 2 = <Q 2, I, δ 2, q 02, F 2 > <A1, A2>= <Q 1 xq 2,I,δ,<q 01,q 02 >,F 1 xq 2 UQ 1 xf 2 > δ(<q 1,q 2 >, i) = <δ 1 (q 1, i), δ 2 (q 2,i)>
36 Complement (1) Basic idea F c = Q-F q 0 q 1 1 but in general the transition function is partial!
37 Complement (2) Before swapping final and non final states it is necessary to complete the FSA q 0 q q 0 q q 0 q 1 q E 0,1 1 0,1 q E 1
38 Union again Another possibility is to use complement and De Morgan s laws: A B = ( A B)
39 Philosophy of complement If I scan the entire input string, then it suffices to swap yes and no (F with Q-F) If I cannot reach the end of the string, then swapping F with Q-F does not work In the case of FSAs there is an easy workaround (completing the FSA) In general we cannot consider the negative answer to a question as equivalent to the positive answer to the opposite question!
Deterministic Finite Automata (DFAs)
Algorithms & Models of Computation CS/ECE 374, Fall 27 Deterministic Finite Automata (DFAs) Lecture 3 Tuesday, September 5, 27 Sariel Har-Peled (UIUC) CS374 Fall 27 / 36 Part I DFA Introduction Sariel
More informationDeterministic Finite Automata (DFAs)
CS/ECE 374: Algorithms & Models of Computation, Fall 28 Deterministic Finite Automata (DFAs) Lecture 3 September 4, 28 Chandra Chekuri (UIUC) CS/ECE 374 Fall 28 / 33 Part I DFA Introduction Chandra Chekuri
More informationFinite State Automata Design
Finite State Automata Design Nicholas Mainardi 1 Dipartimento di Elettronica e Informazione Politecnico di Milano nicholas.mainardi@polimi.it March 14, 2017 1 Mostly based on Alessandro Barenghi s material,
More informationClosure under the Regular Operations
Closure under the Regular Operations Application of NFA Now we use the NFA to show that collection of regular languages is closed under regular operations union, concatenation, and star Earlier we have
More informationDeterministic Finite Automata (DFAs)
Algorithms & Models of Computation CS/ECE 374, Spring 29 Deterministic Finite Automata (DFAs) Lecture 3 Tuesday, January 22, 29 L A TEXed: December 27, 28 8:25 Chan, Har-Peled, Hassanieh (UIUC) CS374 Spring
More informationFinite State Transducers
Finite State Transducers Eric Gribkoff May 29, 2013 Original Slides by Thomas Hanneforth (Universitat Potsdam) Outline 1 Definition of Finite State Transducer 2 Examples of FSTs 3 Definition of Regular
More informationPart I: Definitions and Properties
Turing Machines Part I: Definitions and Properties Finite State Automata Deterministic Automata (DFSA) M = {Q, Σ, δ, q 0, F} -- Σ = Symbols -- Q = States -- q 0 = Initial State -- F = Accepting States
More informationDeterministic Finite Automata (DFAs)
Algorithms & Models of Computation CS/ECE 374, Fall 27 Deterministic Finite Automata (DFAs) Lecture 3 Tuesday, September 5, 27 Part I DFA Introduction Sariel Har-Peled (UIUC) CS374 Fall 27 / 36 Sariel
More informationSri vidya college of engineering and technology
Unit I FINITE AUTOMATA 1. Define hypothesis. The formal proof can be using deductive proof and inductive proof. The deductive proof consists of sequence of statements given with logical reasoning in order
More informationCS 154. Finite Automata, Nondeterminism, Regular Expressions
CS 54 Finite Automata, Nondeterminism, Regular Expressions Read string left to right The DFA accepts a string if the process ends in a double circle A DFA is a 5-tuple M = (Q, Σ, δ, q, F) Q is the set
More informationUses of finite automata
Chapter 2 :Finite Automata 2.1 Finite Automata Automata are computational devices to solve language recognition problems. Language recognition problem is to determine whether a word belongs to a language.
More informationGriffith University 3130CIT Theory of Computation (Based on slides by Harald Søndergaard of The University of Melbourne) Turing Machines 9-0
Griffith University 3130CIT Theory of Computation (Based on slides by Harald Søndergaard of The University of Melbourne) Turing Machines 9-0 Turing Machines Now for a machine model of much greater power.
More informationClosure Properties of Regular Languages. Union, Intersection, Difference, Concatenation, Kleene Closure, Reversal, Homomorphism, Inverse Homomorphism
Closure Properties of Regular Languages Union, Intersection, Difference, Concatenation, Kleene Closure, Reversal, Homomorphism, Inverse Homomorphism Closure Properties Recall a closure property is a statement
More informationFORMAL LANGUAGES, AUTOMATA AND COMPUTABILITY
5-453 FORMAL LANGUAGES, AUTOMATA AND COMPUTABILITY NON-DETERMINISM and REGULAR OPERATIONS THURSDAY JAN 6 UNION THEOREM The union of two regular languages is also a regular language Regular Languages Are
More informationCS 154, Lecture 3: DFA NFA, Regular Expressions
CS 154, Lecture 3: DFA NFA, Regular Expressions Homework 1 is coming out Deterministic Finite Automata Computation with finite memory Non-Deterministic Finite Automata Computation with finite memory and
More informationCS 455/555: Finite automata
CS 455/555: Finite automata Stefan D. Bruda Winter 2019 AUTOMATA (FINITE OR NOT) Generally any automaton Has a finite-state control Scans the input one symbol at a time Takes an action based on the currently
More informationCHAPTER 1 Regular Languages. Contents
Finite Automata (FA or DFA) CHAPTER Regular Languages Contents definitions, examples, designing, regular operations Non-deterministic Finite Automata (NFA) definitions, euivalence of NFAs and DFAs, closure
More informationEquivalence of DFAs and NFAs
CS 172: Computability and Complexity Equivalence of DFAs and NFAs It s a tie! DFA NFA Sanjit A. Seshia EECS, UC Berkeley Acknowledgments: L.von Ahn, L. Blum, M. Blum What we ll do today Prove that DFAs
More informationCS 154, Lecture 2: Finite Automata, Closure Properties Nondeterminism,
CS 54, Lecture 2: Finite Automata, Closure Properties Nondeterminism, Why so Many Models? Streaming Algorithms 0 42 Deterministic Finite Automata Anatomy of Deterministic Finite Automata transition: for
More informationClosure under the Regular Operations
September 7, 2013 Application of NFA Now we use the NFA to show that collection of regular languages is closed under regular operations union, concatenation, and star Earlier we have shown this closure
More informationTheory of Computation p.1/?? Theory of Computation p.2/?? Unknown: Implicitly a Boolean variable: true if a word is
Abstraction of Problems Data: abstracted as a word in a given alphabet. Σ: alphabet, a finite, non-empty set of symbols. Σ : all the words of finite length built up using Σ: Conditions: abstracted as a
More informationCSE 105 Homework 1 Due: Monday October 9, Instructions. should be on each page of the submission.
CSE 5 Homework Due: Monday October 9, 7 Instructions Upload a single file to Gradescope for each group. should be on each page of the submission. All group members names and PIDs Your assignments in this
More informationChapter 3. Regular grammars
Chapter 3 Regular grammars 59 3.1 Introduction Other view of the concept of language: not the formalization of the notion of effective procedure, but set of words satisfying a given set of rules Origin
More informationIntroduction to Turing Machines. Reading: Chapters 8 & 9
Introduction to Turing Machines Reading: Chapters 8 & 9 1 Turing Machines (TM) Generalize the class of CFLs: Recursively Enumerable Languages Recursive Languages Context-Free Languages Regular Languages
More informationIntroduction to Automata
Introduction to Automata Seungjin Choi Department of Computer Science and Engineering Pohang University of Science and Technology 77 Cheongam-ro, Nam-gu, Pohang 37673, Korea seungjin@postech.ac.kr 1 /
More informationFS Properties and FSTs
FS Properties and FSTs Chris Dyer Algorithms for NLP 11-711 Announcements HW1 has been posted; due in class in 2 weeks Goals of Today s Lecture Understand properties of regular languages Understand Brzozowski
More informationCS 154. Finite Automata vs Regular Expressions, Non-Regular Languages
CS 154 Finite Automata vs Regular Expressions, Non-Regular Languages Deterministic Finite Automata Computation with finite memory Non-Deterministic Finite Automata Computation with finite memory and guessing
More informationTuring Machines (TM) Deterministic Turing Machine (DTM) Nondeterministic Turing Machine (NDTM)
Turing Machines (TM) Deterministic Turing Machine (DTM) Nondeterministic Turing Machine (NDTM) 1 Deterministic Turing Machine (DTM).. B B 0 1 1 0 0 B B.. Finite Control Two-way, infinite tape, broken into
More informationIncreasing the power of FSAs
PDA 1 Increasing the power of FSAs The mechanical view Input tape Finite state control device Output tape PDA 2 Now let us enrich it : a Input tape stack memory Finite state control device x q Output tape
More informationProving languages to be nonregular
Proving languages to be nonregular We already know that there exist languages A Σ that are nonregular, for any choice of an alphabet Σ. This is because there are uncountably many languages in total and
More informationAutomata Theory. Lecture on Discussion Course of CS120. Runzhe SJTU ACM CLASS
Automata Theory Lecture on Discussion Course of CS2 This Lecture is about Mathematical Models of Computation. Why Should I Care? - Ways of thinking. - Theory can drive practice. - Don t be an Instrumentalist.
More informationCS 121, Section 2. Week of September 16, 2013
CS 121, Section 2 Week of September 16, 2013 1 Concept Review 1.1 Overview In the past weeks, we have examined the finite automaton, a simple computational model with limited memory. We proved that DFAs,
More informationComputational Models - Lecture 3
Slides modified by Benny Chor, based on original slides by Maurice Herlihy, Brown University. p. 1 Computational Models - Lecture 3 Equivalence of regular expressions and regular languages (lukewarm leftover
More informationComputational Models - Lecture 4
Computational Models - Lecture 4 Regular languages: The Myhill-Nerode Theorem Context-free Grammars Chomsky Normal Form Pumping Lemma for context free languages Non context-free languages: Examples Push
More informationLanguages. Non deterministic finite automata with ε transitions. First there was the DFA. Finite Automata. Non-Deterministic Finite Automata (NFA)
Languages Non deterministic finite automata with ε transitions Recall What is a language? What is a class of languages? Finite Automata Consists of A set of states (Q) A start state (q o ) A set of accepting
More informationFinite-state Machines: Theory and Applications
Finite-state Machines: Theory and Applications Unweighted Finite-state Automata Thomas Hanneforth Institut für Linguistik Universität Potsdam December 10, 2008 Thomas Hanneforth (Universität Potsdam) Finite-state
More informationJohns Hopkins Math Tournament Proof Round: Automata
Johns Hopkins Math Tournament 2018 Proof Round: Automata February 9, 2019 Problem Points Score 1 10 2 5 3 10 4 20 5 20 6 15 7 20 Total 100 Instructions The exam is worth 100 points; each part s point value
More informationFormal Definition of Computation. August 28, 2013
August 28, 2013 Computation model The model of computation considered so far is the work performed by a finite automaton Finite automata were described informally, using state diagrams, and formally, as
More informationSeptember 11, Second Part of Regular Expressions Equivalence with Finite Aut
Second Part of Regular Expressions Equivalence with Finite Automata September 11, 2013 Lemma 1.60 If a language is regular then it is specified by a regular expression Proof idea: For a given regular language
More informationT (s, xa) = T (T (s, x), a). The language recognized by M, denoted L(M), is the set of strings accepted by M. That is,
Recall A deterministic finite automaton is a five-tuple where S is a finite set of states, M = (S, Σ, T, s 0, F ) Σ is an alphabet the input alphabet, T : S Σ S is the transition function, s 0 S is the
More informationCISC 4090: Theory of Computation Chapter 1 Regular Languages. Section 1.1: Finite Automata. What is a computer? Finite automata
CISC 4090: Theory of Computation Chapter Regular Languages Xiaolan Zhang, adapted from slides by Prof. Werschulz Section.: Finite Automata Fordham University Department of Computer and Information Sciences
More information1 More finite deterministic automata
CS 125 Section #6 Finite automata October 18, 2016 1 More finite deterministic automata Exercise. Consider the following game with two players: Repeatedly flip a coin. On heads, player 1 gets a point.
More informationPumping Lemma for CFLs
Pumping Lemma for CFLs v y s Here we go again! Intuition: If L is CF, then some CFG G produces strings in L If some string in L is very long, it will have a very tall parse tree If a parse tree is taller
More informationCS:4330 Theory of Computation Spring Regular Languages. Finite Automata and Regular Expressions. Haniel Barbosa
CS:4330 Theory of Computation Spring 2018 Regular Languages Finite Automata and Regular Expressions Haniel Barbosa Readings for this lecture Chapter 1 of [Sipser 1996], 3rd edition. Sections 1.1 and 1.3.
More informationCS21 Decidability and Tractability
CS21 Decidability and Tractability Lecture 8 January 24, 2018 Outline Turing Machines and variants multitape TMs nondeterministic TMs Church-Turing Thesis So far several models of computation finite automata
More informationThe Pumping Lemma and Closure Properties
The Pumping Lemma and Closure Properties Mridul Aanjaneya Stanford University July 5, 2012 Mridul Aanjaneya Automata Theory 1/ 27 Tentative Schedule HW #1: Out (07/03), Due (07/11) HW #2: Out (07/10),
More informationTAFL 1 (ECS-403) Unit- II. 2.1 Regular Expression: The Operators of Regular Expressions: Building Regular Expressions
TAFL 1 (ECS-403) Unit- II 2.1 Regular Expression: 2.1.1 The Operators of Regular Expressions: 2.1.2 Building Regular Expressions 2.1.3 Precedence of Regular-Expression Operators 2.1.4 Algebraic laws for
More informationV Honors Theory of Computation
V22.0453-001 Honors Theory of Computation Problem Set 3 Solutions Problem 1 Solution: The class of languages recognized by these machines is the exactly the class of regular languages, thus this TM variant
More informationAutomata Theory and Formal Grammars: Lecture 1
Automata Theory and Formal Grammars: Lecture 1 Sets, Languages, Logic Automata Theory and Formal Grammars: Lecture 1 p.1/72 Sets, Languages, Logic Today Course Overview Administrivia Sets Theory (Review?)
More informationFORMAL LANGUAGES, AUTOMATA AND COMPUTABILITY
15-453 FORMAL LANGUAGES, AUTOMATA AND COMPUTABILITY Chomsky Normal Form and TURING MACHINES TUESDAY Feb 4 CHOMSKY NORMAL FORM A context-free grammar is in Chomsky normal form if every rule is of the form:
More informationCSE 105 THEORY OF COMPUTATION. Spring 2018 review class
CSE 105 THEORY OF COMPUTATION Spring 2018 review class Today's learning goals Summarize key concepts, ideas, themes from CSE 105. Approach your final exam studying with confidence. Identify areas to focus
More informationCSE 105 THEORY OF COMPUTATION
CSE 105 THEORY OF COMPUTATION "Winter" 2018 http://cseweb.ucsd.edu/classes/wi18/cse105-ab/ Today's learning goals Sipser Section 1.4 Explain the limits of the class of regular languages Justify why the
More informationTURING MAHINES
15-453 TURING MAHINES TURING MACHINE FINITE STATE q 10 CONTROL AI N P U T INFINITE TAPE read write move 0 0, R, R q accept, R q reject 0 0, R 0 0, R, L read write move 0 0, R, R q accept, R 0 0, R 0 0,
More informationLecture Notes On THEORY OF COMPUTATION MODULE -1 UNIT - 2
BIJU PATNAIK UNIVERSITY OF TECHNOLOGY, ODISHA Lecture Notes On THEORY OF COMPUTATION MODULE -1 UNIT - 2 Prepared by, Dr. Subhendu Kumar Rath, BPUT, Odisha. UNIT 2 Structure NON-DETERMINISTIC FINITE AUTOMATA
More informationWhat we have done so far
What we have done so far DFAs and regular languages NFAs and their equivalence to DFAs Regular expressions. Regular expressions capture exactly regular languages: Construct a NFA from a regular expression.
More informationProofs, Strings, and Finite Automata. CS154 Chris Pollett Feb 5, 2007.
Proofs, Strings, and Finite Automata CS154 Chris Pollett Feb 5, 2007. Outline Proofs and Proof Strategies Strings Finding proofs Example: For every graph G, the sum of the degrees of all the nodes in G
More informationNondeterministic finite automata
Lecture 3 Nondeterministic finite automata This lecture is focused on the nondeterministic finite automata (NFA) model and its relationship to the DFA model. Nondeterminism is an important concept in the
More informationTheory of Computation (I) Yijia Chen Fudan University
Theory of Computation (I) Yijia Chen Fudan University Instructor Yijia Chen Homepage: http://basics.sjtu.edu.cn/~chen Email: yijiachen@fudan.edu.cn Textbook Introduction to the Theory of Computation Michael
More informationCritical CS Questions
Slides modified by Benny Chor, based on original slides by Maurice Herlihy, Brown University. p. 1 Critical CS Questions What is a computer? And What is a Computation? real computers too complex for any
More informationTheory of Computation (II) Yijia Chen Fudan University
Theory of Computation (II) Yijia Chen Fudan University Review A language L is a subset of strings over an alphabet Σ. Our goal is to identify those languages that can be recognized by one of the simplest
More informationComputational Models - Lecture 5 1
Computational Models - Lecture 5 1 Handout Mode Iftach Haitner and Yishay Mansour. Tel Aviv University. April 10/22, 2013 1 Based on frames by Benny Chor, Tel Aviv University, modifying frames by Maurice
More informationHow do regular expressions work? CMSC 330: Organization of Programming Languages
How do regular expressions work? CMSC 330: Organization of Programming Languages Regular Expressions and Finite Automata What we ve learned What regular expressions are What they can express, and cannot
More informationGEETANJALI INSTITUTE OF TECHNICAL STUDIES, UDAIPUR I
GEETANJALI INSTITUTE OF TECHNICAL STUDIES, UDAIPUR I Internal Examination 2017-18 B.Tech III Year VI Semester Sub: Theory of Computation (6CS3A) Time: 1 Hour 30 min. Max Marks: 40 Note: Attempt all three
More informationAnnouncements. Problem Set 6 due next Monday, February 25, at 12:50PM. Midterm graded, will be returned at end of lecture.
Turing Machines Hello Hello Condensed Slide Slide Readers! Readers! This This lecture lecture is is almost almost entirely entirely animations that that show show how how each each Turing Turing machine
More informationarxiv: v2 [cs.fl] 29 Nov 2013
A Survey of Multi-Tape Automata Carlo A. Furia May 2012 arxiv:1205.0178v2 [cs.fl] 29 Nov 2013 Abstract This paper summarizes the fundamental expressiveness, closure, and decidability properties of various
More informationComputational Models: Class 3
Computational Models: Class 3 Benny Chor School of Computer Science Tel Aviv University November 2, 2015 Based on slides by Maurice Herlihy, Brown University, and modifications by Iftach Haitner and Yishay
More informationDecidability (What, stuff is unsolvable?)
University of Georgia Fall 2014 Outline Decidability Decidable Problems for Regular Languages Decidable Problems for Context Free Languages The Halting Problem Countable and Uncountable Sets Diagonalization
More informationIntroduction to the Theory of Computation. Automata 1VO + 1PS. Lecturer: Dr. Ana Sokolova.
Introduction to the Theory of Computation Automata 1VO + 1PS Lecturer: Dr. Ana Sokolova http://cs.uni-salzburg.at/~anas/ Setup and Dates Lectures and Instructions 23.10. 3.11. 17.11. 24.11. 1.12. 11.12.
More informationExamples of Regular Expressions. Finite Automata vs. Regular Expressions. Example of Using flex. Application
Examples of Regular Expressions 1. 0 10, L(0 10 ) = {w w contains exactly a single 1} 2. Σ 1Σ, L(Σ 1Σ ) = {w w contains at least one 1} 3. Σ 001Σ, L(Σ 001Σ ) = {w w contains the string 001 as a substring}
More informationFurther discussion of Turing machines
Further discussion of Turing machines In this lecture we will discuss various aspects of decidable and Turing-recognizable languages that were not mentioned in previous lectures. In particular, we will
More informationFormal Models in NLP
Formal Models in NLP Finite-State Automata Nina Seemann Universität Stuttgart Institut für Maschinelle Sprachverarbeitung Pfaffenwaldring 5b 70569 Stuttgart May 15, 2012 Nina Seemann (IMS) Formal Models
More informationNon-deterministic Finite Automata (NFAs)
Algorithms & Models of Computation CS/ECE 374, Fall 27 Non-deterministic Finite Automata (NFAs) Part I NFA Introduction Lecture 4 Thursday, September 7, 27 Sariel Har-Peled (UIUC) CS374 Fall 27 / 39 Sariel
More informationOpleiding Informatica
Opleiding Informatica Tape-quantifying Turing machines in the arithmetical hierarchy Simon Heijungs Supervisors: H.J. Hoogeboom & R. van Vliet BACHELOR THESIS Leiden Institute of Advanced Computer Science
More informationUNIT-II. NONDETERMINISTIC FINITE AUTOMATA WITH ε TRANSITIONS: SIGNIFICANCE. Use of ε-transitions. s t a r t. ε r. e g u l a r
Syllabus R9 Regulation UNIT-II NONDETERMINISTIC FINITE AUTOMATA WITH ε TRANSITIONS: In the automata theory, a nondeterministic finite automaton (NFA) or nondeterministic finite state machine is a finite
More informationTheory of Computation 1 Sets and Regular Expressions
Theory of Computation 1 Sets and Regular Expressions Frank Stephan Department of Computer Science Department of Mathematics National University of Singapore fstephan@comp.nus.edu.sg Theory of Computation
More informationFinite Automata and Regular languages
Finite Automata and Regular languages Huan Long Shanghai Jiao Tong University Acknowledgements Part of the slides comes from a similar course in Fudan University given by Prof. Yijia Chen. http://basics.sjtu.edu.cn/
More informationPS2 - Comments. University of Virginia - cs3102: Theory of Computation Spring 2010
University of Virginia - cs3102: Theory of Computation Spring 2010 PS2 - Comments Average: 77.4 (full credit for each question is 100 points) Distribution (of 54 submissions): 90, 12; 80 89, 11; 70-79,
More informationCSE 105 THEORY OF COMPUTATION
CSE 105 THEORY OF COMPUTATION Spring 2016 http://cseweb.ucsd.edu/classes/sp16/cse105-ab/ Today's learning goals Sipser Ch 2 Design a PDA and a CFG for a given language Give informal description for a PDA,
More informationProperties of Context-Free Languages. Closure Properties Decision Properties
Properties of Context-Free Languages Closure Properties Decision Properties 1 Closure Properties of CFL s CFL s are closed under union, concatenation, and Kleene closure. Also, under reversal, homomorphisms
More informationTime Magazine (1984)
Time Magazine (1984) Put the right kind of software into a computer, and it will do whatever you want it to. There may be limits on what you can do with the machines themselves, but there are no limits
More informationIntroduction to the Theory of Computation. Automata 1VO + 1PS. Lecturer: Dr. Ana Sokolova.
Introduction to the Theory of Computation Automata 1VO + 1PS Lecturer: Dr. Ana Sokolova http://cs.uni-salzburg.at/~anas/ Setup and Dates Lectures Tuesday 10:45 pm - 12:15 pm Instructions Tuesday 12:30
More informationFooling Sets and. Lecture 5
Fooling Sets and Introduction to Nondeterministic Finite Automata Lecture 5 Proving that a language is not regular Given a language, we saw how to prove it is regular (union, intersection, concatenation,
More informationUNIT-III REGULAR LANGUAGES
Syllabus R9 Regulation REGULAR EXPRESSIONS UNIT-III REGULAR LANGUAGES Regular expressions are useful for representing certain sets of strings in an algebraic fashion. In arithmetic we can use the operations
More informationFORMAL LANGUAGES, AUTOMATA AND COMPUTABILITY
15-453 FORMAL LANGUAGES, AUTOMATA AND COMPUTABILITY REVIEW for MIDTERM 1 THURSDAY Feb 6 Midterm 1 will cover everything we have seen so far The PROBLEMS will be from Sipser, Chapters 1, 2, 3 It will be
More informationAC68 FINITE AUTOMATA & FORMULA LANGUAGES DEC 2013
Q.2 a. Prove by mathematical induction n 4 4n 2 is divisible by 3 for n 0. Basic step: For n = 0, n 3 n = 0 which is divisible by 3. Induction hypothesis: Let p(n) = n 3 n is divisible by 3. Induction
More informationNondeterminism and Epsilon Transitions
Nondeterminism and Epsilon Transitions Mridul Aanjaneya Stanford University June 28, 22 Mridul Aanjaneya Automata Theory / 3 Challenge Problem Question Prove that any square with side length a power of
More informationTDDD65 Introduction to the Theory of Computation
TDDD65 Introduction to the Theory of Computation Lecture 2 Gustav Nordh, IDA gustav.nordh@liu.se 2012-08-31 Outline - Lecture 2 Closure properties of regular languages Regular expressions Equivalence of
More informationComputational Theory
Computational Theory Finite Automata and Regular Languages Curtis Larsen Dixie State University Computing and Design Fall 2018 Adapted from notes by Russ Ross Adapted from notes by Harry Lewis Curtis Larsen
More informationThe Turing Machine. CSE 211 (Theory of Computation) The Turing Machine continued. Turing Machines
The Turing Machine Turing Machines Professor Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka-1000, Bangladesh The Turing machine is essentially
More informationTHEORY OF COMPUTATION (AUBER) EXAM CRIB SHEET
THEORY OF COMPUTATION (AUBER) EXAM CRIB SHEET Regular Languages and FA A language is a set of strings over a finite alphabet Σ. All languages are finite or countably infinite. The set of all languages
More informationFundamentals of Computer Science
Fundamentals of Computer Science Chapter 8: Turing machines Henrik Björklund Umeå University February 17, 2014 The power of automata Finite automata have only finite memory. They recognize the regular
More information3515ICT: Theory of Computation. Regular languages
3515ICT: Theory of Computation Regular languages Notation and concepts concerning alphabets, strings and languages, and identification of languages with problems (H, 1.5). Regular expressions (H, 3.1,
More informationThe tape of M. Figure 3: Simulation of a Turing machine with doubly infinite tape
UG3 Computability and Intractability (2009-2010): Note 4 4. Bells and whistles. In defining a formal model of computation we inevitably make a number of essentially arbitrary design decisions. These decisions
More informationFinite Automata. Finite Automata
Finite Automata Finite Automata Formal Specification of Languages Generators Grammars Context-free Regular Regular Expressions Recognizers Parsers, Push-down Automata Context Free Grammar Finite State
More informationNPDA, CFG equivalence
NPDA, CFG equivalence Theorem A language L is recognized by a NPDA iff L is described by a CFG. Must prove two directions: ( ) L is recognized by a NPDA implies L is described by a CFG. ( ) L is described
More informationTuring machines Finite automaton no storage Pushdown automaton storage is a stack What if we give the automaton a more flexible storage?
Turing machines Finite automaton no storage Pushdown automaton storage is a stack What if we give the automaton a more flexible storage? What is the most powerful of automata? In this lecture we will introduce
More informationCSE 20. Final Review. CSE 20: Final Review
CSE 20 Final Review Final Review Representation of integers in base b Logic Proof systems: Direct Proof Proof by contradiction Contraposetive Sets Theory Functions Induction Final Review Representation
More informationIntroduction: Computer Science is a cluster of related scientific and engineering disciplines concerned with the study and application of computations. These disciplines range from the pure and basic scientific
More informationCPS 220 Theory of Computation
CPS 22 Theory of Computation Review - Regular Languages RL - a simple class of languages that can be represented in two ways: 1 Machine description: Finite Automata are machines with a finite number of
More informationUNIT II REGULAR LANGUAGES
1 UNIT II REGULAR LANGUAGES Introduction: A regular expression is a way of describing a regular language. The various operations are closure, union and concatenation. We can also find the equivalent regular
More information