Chapter 1 Welcome Aboard

Size: px
Start display at page:

Download "Chapter 1 Welcome Aboard"

Transcription

1 Chapter 1 Welcome Aboard

2 Abstraction Interface Source:

3 evels of Abstraction (Biological System) Source: 1-3

4 Copyright The McGraw-Hill Companies, Inc. Permission required for reproduction or display. evels of Abstraction (Computer) Problems Algorithms anguage Instruction Set Architecture Hardware/Software Interface Microarchitecture Circuits Devices 1-4

5 Universal Computing Device All computers, given enough time and memory, are capable of computing exactly the same things. = = Embedded Processor Supercomputer Source: Then what is the simplest possible computing device? 1-5

6 Copyright The McGraw-Hill Companies, Inc. Permission required for reproduction or display. Turing Machine Mathematical model of a device that can perform any computation Alan Turing (1937) Every computation can be performed by some Turing machine. (Turing s thesis) ( 그럼이세상에계산하지못하는것도있나? Yes Halting Problem We ll discuss it later) For more info about Turing machines, see For more about Alan Turing, see 1-6

7 Tape... A Turing Machine... Control Unit ead-write head Source: Prof. Costas Busch s ecture Slides 1-7

8 The Tape... No boundaries -- infinite length... ead-write head The head moves eft or ight Source: Prof. Costas Busch s ecture Slides

9 ead-write head The head at each transition (time step): 1. eads a symbol 2. Writes a symbol 3. Moves eft or ight Source: Prof. Costas Busch s ecture Slides

10 Example:... Time 0 a a c b Time 1 a b k c eads 2. Writes a k 3. Moves eft Source: Prof. Costas Busch s ecture Slides

11 Computation Example The function f ( x, y) x y is computable x, y are integers Turing Machine: Input string: x0 y unary Output string: xy0 unary Source: Prof. Costas Busch s ecture Slides

12 x y Start q 0 initial state The 0 is the delimiter that separates the two numbers Source: Prof. Costas Busch s ecture Slides

13 x y Start q 0 initial state x y Finish q f final state Source: Prof. Costas Busch s ecture Slides

14 Execution Example: x 11 y 11 (=2) (=2) q 0 x Time 0 y Final esult x y Source: Prof. Costas Busch s ecture Slides

15 Turing machine for function f ( x, y) x y Control Unit q 0 0 1,, q q ,, Source: Prof. Costas Busch s ecture Slides

16 Time q 0 0 1, q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

17 Time q 0 0 1, q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

18 Time q 0 0 1, q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

19 Time q 1 0 1, q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

20 Time q 1 0 1, q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

21 Time q 1 0 1, q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

22 Time q 1 0 1, q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

23 Time q 2 0 1, q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

24 Time , q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

25 Time , q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

26 Time , q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

27 Time , q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

28 Time , q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

29 Time , q0 1 q, q2 1 0,, Source: Prof. Costas Busch s ecture Slides

30 Time , q0 1 q, q2 1 0, HAT & accept Source: Prof. Costas Busch s ecture Slides

31 Copyright The McGraw-Hill Companies, Inc. Permission required for reproduction or display. Universal Turing Machine A machine that can implement all Turing machines -- this is also a Turing machine! inputs: data, plus a description of computation (other TMs) T add, T mul a,b,c U c(a+b) Universal Turing Machine U is programmable so is a computer! Program is part of the input data a computer can emulate a Universal Turing Machine and vice versa A computer is a universal computing device. 1-31

32 Halting Problem Halting Problem The problem of determining, from a description of an arbitrary computer program (i.e., Turing machine) and an input, whether he program will finish running (i.e., halts) or continue to run forever Halting problem is undecidable (not Turing machine solvable) (Proof by an application of Cantor s diagonal argument) 오토마타교과목에서더깊게다루어짐. 1-32

33 꼭기억해야할것 (evels of) Abstraction Turing Equivalence Undecidable Problem (not Turing machine computable) 1-33

Turing Machines. The Language Hierarchy. Context-Free Languages. Regular Languages. Courtesy Costas Busch - RPI 1

Turing Machines. The Language Hierarchy. Context-Free Languages. Regular Languages. Courtesy Costas Busch - RPI 1 Turing Machines a n b n c The anguage Hierarchy n? ww? Context-Free anguages a n b n egular anguages a * a *b* ww Courtesy Costas Busch - PI a n b n c n Turing Machines anguages accepted by Turing Machines

More information

Busch Complexity Lectures: Turing Machines. Prof. Busch - LSU 1

Busch Complexity Lectures: Turing Machines. Prof. Busch - LSU 1 Busch Complexity ectures: Turing Machines Prof. Busch - SU 1 The anguage Hierarchy a n b n c n? ww? Context-Free anguages n b n a ww egular anguages a* a *b* Prof. Busch - SU 2 a n b anguages accepted

More information

Turing s thesis: (1930) Any computation carried out by mechanical means can be performed by a Turing Machine

Turing s thesis: (1930) Any computation carried out by mechanical means can be performed by a Turing Machine Turing s thesis: (1930) Any computation carried out by mechanical means can be performed by a Turing Machine There is no known model of computation more powerful than Turing Machines Definition of Algorithm:

More information

HIS LEGACY. 100 Years Turing celebration. Gordana Dodig Crnkovic, IDT Open Seminar. Computer Science and Network Department Mälardalen University

HIS LEGACY. 100 Years Turing celebration. Gordana Dodig Crnkovic, IDT Open Seminar. Computer Science and Network Department Mälardalen University IDT Open Seminar AAN TUING AND HIS EGACY 00 Years Turing celebration http://www.mrtc.mdh.se/~gdc/work/turingcentenary.pdf http://www.mrtc.mdh.se/ mdh se/~gdc/work/turingmachine.pdf Gordana Dodig Crnkovic,

More information

Chapter 7 Turing Machines

Chapter 7 Turing Machines Chapter 7 Turing Machines Copyright 2011 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 1 A General Model of Computation Both finite automata and pushdown automata are

More information

Chapter 01: Introduction. Lesson 01 Evolution Computers Part 1: Mechanical Systems, Babbage method of Finite Difference Engine and Turing Hypothesis

Chapter 01: Introduction. Lesson 01 Evolution Computers Part 1: Mechanical Systems, Babbage method of Finite Difference Engine and Turing Hypothesis Chapter 01: Introduction Lesson 01 Evolution Computers Part 1: Mechanical Systems, Babbage method of Finite Difference Engine and Turing Hypothesis Objective Understand how mechanical computation systems

More information

CS20a: Turing Machines (Oct 29, 2002)

CS20a: Turing Machines (Oct 29, 2002) CS20a: Turing Machines (Oct 29, 2002) So far: DFA = regular languages PDA = context-free languages Today: Computability 1 Handicapped machines DFA limitations Tape head moves only one direction 2-way DFA

More information

Turing Machines and the Church-Turing Thesis

Turing Machines and the Church-Turing Thesis CSE2001, Fall 2006 1 Turing Machines and the Church-Turing Thesis Today our goal is to show that Turing Machines are powerful enough to model digital computers, and to see discuss some evidence for the

More information

Decidable Languages - relationship with other classes.

Decidable Languages - relationship with other classes. CSE2001, Fall 2006 1 Last time we saw some examples of decidable languages (or, solvable problems). Today we will start by looking at the relationship between the decidable languages, and the regular and

More information

Turing machine recap. Universal Turing Machines and Undecidability. Alphabet size doesn t matter. Robustness of TM

Turing machine recap. Universal Turing Machines and Undecidability. Alphabet size doesn t matter. Robustness of TM Turing machine recap A Turing machine TM is a tuple M = (Γ, Q, δ) where Γ: set of symbols that TM s tapes can contain. Q: possible states TM can be in. qstart: the TM starts in this state qhalt: the TM

More information

Busch Complexity Lectures: Turing s Thesis. Costas Busch - LSU 1

Busch Complexity Lectures: Turing s Thesis. Costas Busch - LSU 1 Busch Complexity Lectures: Turing s Thesis Costas Busch - LSU 1 Turing s thesis (1930): Any computation carried out by mechanical means can be performed by a Turing Machine Costas Busch - LSU 2 Algorithm:

More information

Turing s Thesis. Fall Costas Busch - RPI!1

Turing s Thesis. Fall Costas Busch - RPI!1 Turing s Thesis Costas Busch - RPI!1 Turing s thesis (1930): Any computation carried out by mechanical means can be performed by a Turing Machine Costas Busch - RPI!2 Algorithm: An algorithm for a problem

More information

Turing Machines. Wolfgang Schreiner

Turing Machines. Wolfgang Schreiner Turing Machines Wolfgang Schreiner Wolfgang.Schreiner@risc.jku.at Research Institute for Symbolic Computation (RISC) Johannes Kepler University, Linz, Austria http://www.risc.jku.at Wolfgang Schreiner

More information

CS20a: Turing Machines (Oct 29, 2002)

CS20a: Turing Machines (Oct 29, 2002) CS20a: Turing Machines (Oct 29, 2002) So far: DFA = regular languages PDA = context-free languages Today: Computability 1 Church s thesis The computable functions are the same as the partial recursive

More information

Theory of Computation (IX) Yijia Chen Fudan University

Theory of Computation (IX) Yijia Chen Fudan University Theory of Computation (IX) Yijia Chen Fudan University Review The Definition of Algorithm Polynomials and their roots A polynomial is a sum of terms, where each term is a product of certain variables and

More information

and Models of Computation

and Models of Computation CDT314 FABE Formal anguages, Automata and Models of Computation ecture 12 Mälardalen University 2013 1 Content Chomsky s anguage Hierarchy Turing Machines Determinism Halting TM Examples Standard TM Computing

More information

Computability and Complexity

Computability and Complexity Computability and Complexity Lecture 5 Reductions Undecidable problems from language theory Linear bounded automata given by Jiri Srba Lecture 5 Computability and Complexity 1/14 Reduction Informal Definition

More information

CS5371 Theory of Computation. Lecture 10: Computability Theory I (Turing Machine)

CS5371 Theory of Computation. Lecture 10: Computability Theory I (Turing Machine) CS537 Theory of Computation Lecture : Computability Theory I (Turing Machine) Objectives Introduce the Turing Machine (TM) Proposed by Alan Turing in 936 finite-state control + infinitely long tape A stronger

More information

CS5371 Theory of Computation. Lecture 10: Computability Theory I (Turing Machine)

CS5371 Theory of Computation. Lecture 10: Computability Theory I (Turing Machine) CS537 Theory of Computation Lecture : Computability Theory I (Turing Machine) Objectives Introduce the Turing Machine (TM)? Proposed by Alan Turing in 936 finite-state control + infinitely long tape A

More information

Equivalence of TMs and Multitape TMs. Theorem 3.13 and Corollary 3.15 By: Joseph Lauman

Equivalence of TMs and Multitape TMs. Theorem 3.13 and Corollary 3.15 By: Joseph Lauman Equivalence of TMs and Multitape TMs Theorem 3.13 and Corollary 3.15 By: Joseph Lauman Turing Machines First proposed by Alan Turing in 1936 Similar to finite automaton, but with an unlimited and unrestricted

More information

1 Showing Recognizability

1 Showing Recognizability CSCC63 Worksheet Recognizability and Decidability 1 1 Showing Recognizability 1.1 An Example - take 1 Let Σ be an alphabet. L = { M M is a T M and L(M) }, i.e., that M accepts some string from Σ. Prove

More information

Undecidable Problems. Z. Sawa (TU Ostrava) Introd. to Theoretical Computer Science May 12, / 65

Undecidable Problems. Z. Sawa (TU Ostrava) Introd. to Theoretical Computer Science May 12, / 65 Undecidable Problems Z. Sawa (TU Ostrava) Introd. to Theoretical Computer Science May 12, 2018 1/ 65 Algorithmically Solvable Problems Let us assume we have a problem P. If there is an algorithm solving

More information

Chapter 3: The Church-Turing Thesis

Chapter 3: The Church-Turing Thesis Chapter 3: The Church-Turing Thesis 1 Turing Machine (TM) Control... Bi-direction Read/Write Turing machine is a much more powerful model, proposed by Alan Turing in 1936. 2 Church/Turing Thesis Anything

More information

V Honors Theory of Computation

V 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 information

highlights proof by contradiction what about the real numbers?

highlights proof by contradiction what about the real numbers? CSE 311: Foundations of Computing Fall 2013 Lecture 27: Turing machines and decidability highlights Cardinality A set S is countableiffwe can writeit as S={s 1, s 2, s 3,...} indexed by N Set of rationals

More information

SE 3310b Theoretical Foundations of Software Engineering. Turing Machines. Aleksander Essex

SE 3310b Theoretical Foundations of Software Engineering. Turing Machines. Aleksander Essex SE 3310b Theoretical Foundations of Software Engineering Turing Machines Aleksander Essex 1 / 1 Turing Machines 2 / 1 Introduction We ve finally arrived at a complete model of computation: Turing machines.

More information

Turing machine. Turing Machine Model. Turing Machines. 1. Turing Machines. Wolfgang Schreiner 2. Recognizing Languages

Turing machine. Turing Machine Model. Turing Machines. 1. Turing Machines. Wolfgang Schreiner 2. Recognizing Languages Turing achines Wolfgang Schreiner Wolfgang.Schreiner@risc.jku.at Research Institute for Symbolic Computation (RISC) Johannes Kepler University, Linz, Austria http://www.risc.jku.at 1. Turing achines Wolfgang

More information

CS 21 Decidability and Tractability Winter Solution Set 3

CS 21 Decidability and Tractability Winter Solution Set 3 CS 21 Decidability and Tractability Winter 2018 Posted: January 31 Solution Set 3 If you have not yet turned in the Problem Set, you should not consult these solutions. 1. (a) A 2-NPDA is a 7-tuple (Q,,

More information

The Turing Machine. Computability. The Church-Turing Thesis (1936) Theory Hall of Fame. Theory Hall of Fame. Undecidability

The Turing Machine. Computability. The Church-Turing Thesis (1936) Theory Hall of Fame. Theory Hall of Fame. Undecidability The Turing Machine Computability Motivating idea Build a theoretical a human computer Likened to a human with a paper and pencil that can solve problems in an algorithmic way The theoretical provides a

More information

CS151 Complexity Theory. Lecture 1 April 3, 2017

CS151 Complexity Theory. Lecture 1 April 3, 2017 CS151 Complexity Theory Lecture 1 April 3, 2017 Complexity Theory Classify problems according to the computational resources required running time storage space parallelism randomness rounds of interaction,

More information

Undecidability COMS Ashley Montanaro 4 April Department of Computer Science, University of Bristol Bristol, UK

Undecidability COMS Ashley Montanaro 4 April Department of Computer Science, University of Bristol Bristol, UK COMS11700 Undecidability Department of Computer Science, University of Bristol Bristol, UK 4 April 2014 COMS11700: Undecidability Slide 1/29 Decidability We are particularly interested in Turing machines

More information

Automata Theory CS S-12 Turing Machine Modifications

Automata Theory CS S-12 Turing Machine Modifications Automata Theory CS411-2015S-12 Turing Machine Modifications David Galles Department of Computer Science University of San Francisco 12-0: Extending Turing Machines When we added a stack to NFA to get a

More information

CSE 105 THEORY OF COMPUTATION

CSE 105 THEORY OF COMPUTATION CSE 105 THEORY OF COMPUTATION Fall 2016 http://cseweb.ucsd.edu/classes/fa16/cse105-abc/ Today's learning goals Sipser Ch 3 Trace the computation of a Turing machine using its transition function and configurations.

More information

The Church-Turing Thesis

The Church-Turing Thesis The Church-Turing Thesis 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 information

Automata & languages. A primer on the Theory of Computation. Laurent Vanbever. ETH Zürich (D-ITET) October,

Automata & languages. A primer on the Theory of Computation. Laurent Vanbever.   ETH Zürich (D-ITET) October, Automata & languages A primer on the Theory of Computation Laurent Vanbever www.vanbever.eu ETH Zürich (D-ITET) October, 19 2017 Part 5 out of 5 Last week was all about Context-Free Languages Context-Free

More information

CS21 Decidability and Tractability

CS21 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 information

CSCE 551: Chin-Tser Huang. University of South Carolina

CSCE 551: Chin-Tser Huang. University of South Carolina CSCE 551: Theory of Computation Chin-Tser Huang huangct@cse.sc.edu University of South Carolina Church-Turing Thesis The definition of the algorithm came in the 1936 papers of Alonzo Church h and Alan

More information

Turing Machines Part III

Turing Machines Part III Turing Machines Part III Announcements Problem Set 6 due now. Problem Set 7 out, due Monday, March 4. Play around with Turing machines, their powers, and their limits. Some problems require Wednesday's

More information

Turing Machines (TM) Deterministic Turing Machine (DTM) Nondeterministic Turing Machine (NDTM)

Turing 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 information

The Power of One-State Turing Machines

The Power of One-State Turing Machines The Power of One-State Turing Machines Marzio De Biasi Jan 15, 2018 Abstract At first glance, one state Turing machines are very weak: the Halting problem for them is decidable, and, without memory, they

More information

Computation. Some history...

Computation. Some history... Computation Motivating questions: What does computation mean? What are the similarities and differences between computation in computers and in natural systems? What are the limits of computation? Are

More information

Turing Machines. Wen-Guey Tzeng Computer Science Department National Chiao Tung University

Turing Machines. Wen-Guey Tzeng Computer Science Department National Chiao Tung University Turing Machines Wen-Guey Tzeng Computer Science Department National Chiao Tung University Alan Turing One of the first to conceive a machine that can run computation mechanically without human intervention.

More information

CpSc 421 Homework 9 Solution

CpSc 421 Homework 9 Solution CpSc 421 Homework 9 Solution Attempt any three of the six problems below. The homework is graded on a scale of 100 points, even though you can attempt fewer or more points than that. Your recorded grade

More information

Turing Machines. Lecture 8

Turing Machines. Lecture 8 Turing Machines Lecture 8 1 Course Trajectory We will see algorithms, what can be done. But what cannot be done? 2 Computation Problem: To compute a function F that maps each input (a string) to an output

More information

A Universal Turing Machine

A Universal Turing Machine A Universal Turing Machine A limitation of Turing Machines: Turing Machines are hardwired they execute only one program Real Computers are re-programmable Solution: Universal Turing Machine Attributes:

More information

TURING MAHINES

TURING 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 information

MACHINE COMPUTING. the limitations

MACHINE COMPUTING. the limitations MACHINE COMPUTING the limitations human computing stealing brain cycles of the masses word recognition: to digitize all printed writing language education: to translate web content games with a purpose

More information

7.2 Turing Machines as Language Acceptors 7.3 Turing Machines that Compute Partial Functions

7.2 Turing Machines as Language Acceptors 7.3 Turing Machines that Compute Partial Functions CSC4510/6510 AUTOMATA 7.1 A General Model of Computation 7.2 Turing Machines as Language Acceptors 7.3 Turing Machines that Compute Partial Functions A General Model of Computation Both FA and PDA are

More information

Computable Functions

Computable Functions Computable Functions Part I: Non Computable Functions Computable and Partially Computable Functions Computable Function Exists a Turing Machine M -- M Halts on All Input -- M(x) = f (x) Partially Computable

More information

Part I: Definitions and Properties

Part 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 information

Midterm Exam 2 CS 341: Foundations of Computer Science II Fall 2016, face-to-face day section Prof. Marvin K. Nakayama

Midterm Exam 2 CS 341: Foundations of Computer Science II Fall 2016, face-to-face day section Prof. Marvin K. Nakayama Midterm Exam 2 CS 341: Foundations of Computer Science II Fall 2016, face-to-face day section Prof. Marvin K. Nakayama Print family (or last) name: Print given (or first) name: I have read and understand

More information

Complexity Theory Turing Machines

Complexity Theory Turing Machines Complexity Theory Turing Machines Joseph Spring Department of Computer Science 3COM0074 - Quantum Computing / QIP QC - Lecture 2 1 Areas for Discussion Algorithms Complexity Theory and Computing Models

More information

CSCI3390-Assignment 2 Solutions

CSCI3390-Assignment 2 Solutions CSCI3390-Assignment 2 Solutions due February 3, 2016 1 TMs for Deciding Languages Write the specification of a Turing machine recognizing one of the following three languages. Do one of these problems.

More information

Decision Problems with TM s. Lecture 31: Halting Problem. Universe of discourse. Semi-decidable. Look at following sets: CSCI 81 Spring, 2012

Decision Problems with TM s. Lecture 31: Halting Problem. Universe of discourse. Semi-decidable. Look at following sets: CSCI 81 Spring, 2012 Decision Problems with TM s Look at following sets: Lecture 31: Halting Problem CSCI 81 Spring, 2012 Kim Bruce A TM = { M,w M is a TM and w L(M)} H TM = { M,w M is a TM which halts on input w} TOTAL TM

More information

Decidability: Church-Turing Thesis

Decidability: Church-Turing Thesis Decidability: Church-Turing Thesis While there are a countably infinite number of languages that are described by TMs over some alphabet Σ, there are an uncountably infinite number that are not Are there

More information

(a) Definition of TMs. First Problem of URMs

(a) Definition of TMs. First Problem of URMs Sec. 4: Turing Machines First Problem of URMs (a) Definition of the Turing Machine. (b) URM computable functions are Turing computable. (c) Undecidability of the Turing Halting Problem That incrementing

More information

CSE355 SUMMER 2018 LECTURES TURING MACHINES AND (UN)DECIDABILITY

CSE355 SUMMER 2018 LECTURES TURING MACHINES AND (UN)DECIDABILITY CSE355 SUMMER 2018 LECTURES TURING MACHINES AND (UN)DECIDABILITY RYAN DOUGHERTY If we want to talk about a program running on a real computer, consider the following: when a program reads an instruction,

More information

There are problems that cannot be solved by computer programs (i.e. algorithms) even assuming unlimited time and space.

There are problems that cannot be solved by computer programs (i.e. algorithms) even assuming unlimited time and space. Undecidability There are problems that cannot be solved by computer programs (i.e. algorithms) even assuming unlimited time and space. Proved by Alan Turing in 1936 What is a computer program/algorithm?

More information

CSCI3390-Lecture 6: An Undecidable Problem

CSCI3390-Lecture 6: An Undecidable Problem CSCI3390-Lecture 6: An Undecidable Problem September 21, 2018 1 Summary The language L T M recognized by the universal Turing machine is not decidable. Thus there is no algorithm that determines, yes or

More information

Theory of Computation. Theory of Computation

Theory of Computation. Theory of Computation Theory of Computation Theory of Computation What is possible to compute? We can prove that there are some problems computers cannot solve There are some problems computers can theoretically solve, but

More information

Introduction to Turing Machines

Introduction to Turing Machines Introduction to Turing Machines Deepak D Souza Department of Computer Science and Automation Indian Institute of Science, Bangalore. 12 November 2015 Outline 1 Turing Machines 2 Formal definitions 3 Computability

More information

Introduction to Turing Machines. Reading: Chapters 8 & 9

Introduction 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 information

Variations of the Turing Machine

Variations of the Turing Machine Variations of the Turing Machine 1 The Standard Model Infinite Tape a a b a b b c a c a Read-Write Head (Left or Right) Control Unit Deterministic 2 Variations of the Standard Model Turing machines with:

More information

CS154, Lecture 10: Rice s Theorem, Oracle Machines

CS154, Lecture 10: Rice s Theorem, Oracle Machines CS154, Lecture 10: Rice s Theorem, Oracle Machines Moral: Analyzing Programs is Really, Really Hard But can we more easily tell when some program analysis problem is undecidable? Problem 1 Undecidable

More information

Turing Machine properties. Turing Machines. Alternate TM definitions. Alternate TM definitions. Alternate TM definitions. Alternate TM definitions

Turing Machine properties. Turing Machines. Alternate TM definitions. Alternate TM definitions. Alternate TM definitions. Alternate TM definitions Turing Machine properties Turing Machines TM Variants and the Universal TM There are many ways to skin a cat And many ways to define a TM The book s Standard Turing Machines Tape unbounded on both sides

More information

IV. Turing Machine. Yuxi Fu. BASICS, Shanghai Jiao Tong University

IV. Turing Machine. Yuxi Fu. BASICS, Shanghai Jiao Tong University IV. Turing Machine Yuxi Fu BASICS, Shanghai Jiao Tong University Alan Turing Alan Turing (23Jun.1912-7Jun.1954), an English student of Church, introduced a machine model for effective calculation in On

More information

Recap (1) 1. Automata, grammars and other formalisms can be considered as mechanical devices to solve mathematical problems

Recap (1) 1. Automata, grammars and other formalisms can be considered as mechanical devices to solve mathematical problems Computability 1 Recap (1) 1. Automata, grammars and other formalisms can be considered as mechanical devices to solve mathematical problems Mathematical problems are often the formalization of some practical

More information

Section 14.1 Computability then else

Section 14.1 Computability then else Section 14.1 Computability Some problems cannot be solved by any machine/algorithm. To prove such statements we need to effectively describe all possible algorithms. Example (Turing machines). Associate

More information

CS 301. Lecture 18 Decidable languages. Stephen Checkoway. April 2, 2018

CS 301. Lecture 18 Decidable languages. Stephen Checkoway. April 2, 2018 CS 301 Lecture 18 Decidable languages Stephen Checkoway April 2, 2018 1 / 26 Decidable language Recall, a language A is decidable if there is some TM M that 1 recognizes A (i.e., L(M) = A), and 2 halts

More information

Reducability. Sipser, pages

Reducability. Sipser, pages Reducability Sipser, pages 187-214 Reduction Reduction encodes (transforms) one problem as a second problem. A solution to the second, can be transformed into a solution to the first. We expect both transformations

More information

Most General computer?

Most General computer? Turing Machines Most General computer? DFAs are simple model of computation. Accept only the regular languages. Is there a kind of computer that can accept any language, or compute any function? Recall

More information

CS154, Lecture 17: conp, Oracles again, Space Complexity

CS154, Lecture 17: conp, Oracles again, Space Complexity CS154, Lecture 17: conp, Oracles again, Space Complexity Definition: conp = { L L NP } What does a conp computation look like? In NP algorithms, we can use a guess instruction in pseudocode: Guess string

More information

There are two main techniques for showing that problems are undecidable: diagonalization and reduction

There are two main techniques for showing that problems are undecidable: diagonalization and reduction Reducibility 1 There are two main techniques for showing that problems are undecidable: diagonalization and reduction 2 We say that a problem A is reduced to a problem B if the decidability of A follows

More information

Announcements. Problem Set 6 due next Monday, February 25, at 12:50PM. Midterm graded, will be returned at end of lecture.

Announcements. 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 information

16.1 Countability. CS125 Lecture 16 Fall 2014

16.1 Countability. CS125 Lecture 16 Fall 2014 CS125 Lecture 16 Fall 2014 16.1 Countability Proving the non-existence of algorithms for computational problems can be very difficult. Indeed, we do not know how to prove P NP. So a natural question is

More information

Universal Turing Machine. Lecture 20

Universal Turing Machine. Lecture 20 Universal Turing Machine Lecture 20 1 Turing Machine move the head left or right by one cell read write sequentially accessed infinite memory finite memory (state) next-action look-up table Variants don

More information

Introduction to Computer Science

Introduction to Computer Science Introduction to Computer Science CSCI 109 China Tianhe-2 Andrew Goodney Fall 2017 Lecture 11: Abstract Machines and Theory Nov. 13th, 2017 Schedule 1 Abstract machines and theory uwhat is theoretical computer

More information

Computation Histories

Computation Histories 208 Computation Histories The computation history for a Turing machine on an input is simply the sequence of configurations that the machine goes through as it processes the input. An accepting computation

More information

ELEMENTS IN MATHEMATICS FOR INFORMATION SCIENCE NO.6 TURING MACHINE AND COMPUTABILITY. Tatsuya Hagino

ELEMENTS IN MATHEMATICS FOR INFORMATION SCIENCE NO.6 TURING MACHINE AND COMPUTABILITY. Tatsuya Hagino 1 ELEMENTS IN MATHEMATICS FOR INFORMATION SCIENCE NO.6 TURING MACHINE AND COMPUTABILITY Tatsuya Hagino hagino@sfc.keio.ac.jp 2 So far Computation flow chart program while program recursive function primitive

More information

15-251: Great Theoretical Ideas in Computer Science Fall 2016 Lecture 6 September 15, Turing & the Uncomputable

15-251: Great Theoretical Ideas in Computer Science Fall 2016 Lecture 6 September 15, Turing & the Uncomputable 15-251: Great Theoretical Ideas in Computer Science Fall 2016 Lecture 6 September 15, 2016 Turing & the Uncomputable Comparing the cardinality of sets A B if there is an injection (one-to-one map) from

More information

CS5371 Theory of Computation. Lecture 14: Computability V (Prove by Reduction)

CS5371 Theory of Computation. Lecture 14: Computability V (Prove by Reduction) CS5371 Theory of Computation Lecture 14: Computability V (Prove by Reduction) Objectives This lecture shows more undecidable languages Our proof is not based on diagonalization Instead, we reduce the problem

More information

Turing Machines Part II

Turing Machines Part II Turing Machines Part II COMP2600 Formal Methods for Software Engineering Katya Lebedeva Australian National University Semester 2, 2016 Slides created by Katya Lebedeva COMP 2600 Turing Machines 1 Why

More information

1 Unrestricted Computation

1 Unrestricted Computation 1 Unrestricted Computation General Computing Machines Machines so far: DFAs, NFAs, PDAs Limitations on how much memory they can use: fixed amount of memory plus (for PDAs) a stack Limitations on what they

More information

CMPT 710/407 - Complexity Theory Lecture 4: Complexity Classes, Completeness, Linear Speedup, and Hierarchy Theorems

CMPT 710/407 - Complexity Theory Lecture 4: Complexity Classes, Completeness, Linear Speedup, and Hierarchy Theorems CMPT 710/407 - Complexity Theory Lecture 4: Complexity Classes, Completeness, Linear Speedup, and Hierarchy Theorems Valentine Kabanets September 13, 2007 1 Complexity Classes Unless explicitly stated,

More information

Analysis of Algorithms. Unit 5 - Intractable Problems

Analysis of Algorithms. Unit 5 - Intractable Problems Analysis of Algorithms Unit 5 - Intractable Problems 1 Intractable Problems Tractable Problems vs. Intractable Problems Polynomial Problems NP Problems NP Complete and NP Hard Problems 2 In this unit we

More information

Decidability (What, stuff is unsolvable?)

Decidability (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 information

Griffith 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 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 information

Lecture Notes: The Halting Problem; Reductions

Lecture Notes: The Halting Problem; Reductions Lecture Notes: The Halting Problem; Reductions COMS W3261 Columbia University 20 Mar 2012 1 Review Key point. Turing machines can be encoded as strings, and other Turing machines can read those strings

More information

Theory of Computation

Theory of Computation Thomas Zeugmann Hokkaido University Laboratory for Algorithmics http://www-alg.ist.hokudai.ac.jp/ thomas/toc/ Lecture 13: Algorithmic Unsolvability The Halting Problem I In the last lecture we have shown

More information

4.2 The Halting Problem

4.2 The Halting Problem 172 4.2 The Halting Problem The technique of diagonalization was discovered in 1873 by Georg Cantor who was concerned with the problem of measuring the sizes of infinite sets For finite sets we can simply

More information

Fundamentals of Computer Science

Fundamentals 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 information

problem X reduces to Problem Y solving X would be easy, if we knew how to solve Y

problem X reduces to Problem Y solving X would be easy, if we knew how to solve Y CPS220 Reducibility A reduction is a procedure to convert one problem to another problem, in such a way that a solution to the second problem can be used to solve the first problem. The conversion itself

More information

Turing Machine Variants

Turing Machine Variants CS311 Computational Structures Turing Machine Variants Lecture 12 Andrew Black Andrew Tolmach 1 The Church-Turing Thesis The problems that can be decided by an algorithm are exactly those that can be decided

More information

The purpose here is to classify computational problems according to their complexity. For that purpose we need first to agree on a computational

The purpose here is to classify computational problems according to their complexity. For that purpose we need first to agree on a computational 1 The purpose here is to classify computational problems according to their complexity. For that purpose we need first to agree on a computational model. We'll remind you what a Turing machine is --- you

More information

Non-emptiness Testing for TMs

Non-emptiness Testing for TMs 180 5. Reducibility The proof of unsolvability of the halting problem is an example of a reduction: a way of converting problem A to problem B in such a way that a solution to problem B can be used to

More information

Undecidability. Andreas Klappenecker. [based on slides by Prof. Welch]

Undecidability. Andreas Klappenecker. [based on slides by Prof. Welch] Undecidability Andreas Klappenecker [based on slides by Prof. Welch] 1 Sources Theory of Computing, A Gentle Introduction, by E. Kinber and C. Smith, Prentice-Hall, 2001 Automata Theory, Languages and

More information

conp, Oracles, Space Complexity

conp, Oracles, Space Complexity conp, Oracles, Space Complexity 1 What s next? A few possibilities CS161 Design and Analysis of Algorithms CS254 Complexity Theory (next year) CS354 Topics in Circuit Complexity For your favorite course

More information

Models. Models of Computation, Turing Machines, and the Limits of Turing Computation. Effective Calculability. Motivation for Models of Computation

Models. Models of Computation, Turing Machines, and the Limits of Turing Computation. Effective Calculability. Motivation for Models of Computation Turing Computation /0/ Models of Computation, Turing Machines, and the Limits of Turing Computation Bruce MacLennan Models A model is a tool intended to address a class of questions about some domain of

More information

1 Reals are Uncountable

1 Reals are Uncountable CS 30: Discrete Math in CS (Winter 2019): Lecture 6 Date: 11th January, 2019 (Friday) Topic: Uncountability and Undecidability Disclaimer: These notes have not gone through scrutiny and in all probability

More information

CS154 Final Examination

CS154 Final Examination CS154 Final Examination June 7, 2010, 7-10PM Directions: CS154 students: answer all 13 questions on this paper. Those taking CS154N should answer only questions 8-13. The total number of points on this

More information