Examples of Unlimited Register Machine programs for Turingcomputable

Size: px
Start display at page:

Download "Examples of Unlimited Register Machine programs for Turingcomputable"

Transcription

1 Examples of Unlimited Register Machine programs for Turingcomputable functions 18 February 2012 at 13:01 Public It will be a matter of interest for me over the next few months to formulate (and collect) numerous examples of basic URM programs to implement simple Turing-computable functions. I'll do this here. Background: Unlimited Register Machines (URMs) were introduced into the mathematical literature in the early 1960s as an easier version of Turing machines to work with. (Detailed history and references can be found here: Turing machines (and URMs) are idealized computers for the study of the algorithmic computability of functions. The idea is that not all functions are able to be computed algorithmically. Those functions that ARE algorithmically computable are called Turing-computable and for such functions it is possible to write a program which will implement them on a Turing machine (or equivalently a URM) in a finite number of steps. According to the famous Church-Turing Thesis, the class of algorithmically computable functions is precisely the class of functions which are recursive (a recursive function is one that can be obtained from certain more basic functions by certain elementary operations implemented a finite number of times). I want to use this note to practise formulating (and also just to collect) specific examples of short URM programs which will implement simple Turing-computable functions. The basic features of the type of URM programs I am interested in are summarised in the following printed note (the sample URM program given here is one that performs addition of two numbers):

2

3

4 EXAMPLE 1 The following URM program computes three partial functions which I will discuss below (a partial function is a function whose domain is a subset of Nᵏ, the k-dimensional Cartesian product of the set of natural numbers. A function whose domain is the whole of Nᵏ is a total function): 1. J(1, 3, 6) 2. S(2) 3. S(2) 4. S(3) 5. J(1, 1, 1) 6. C(2, 1) This is what one obtains when this program is implemented with the input (2, 1, 1):

5 To work out the partial function f¹ we consider an initial input n. In the first pass we would have R 2 go from 0 to 2, and R 3 go from 0 to 1. In the next pass R 2 goes to 4, and R 3 goes to 2. This continues until R 2 contains 2n and R 3 contains n. This will occur for any non-negative n, so this partial function is actually total and we have f¹(n) = 2n. To work out the partial function f² we consider an initial input (n 1, n 2 ). In the first pass we would have R 2 go from n 2 to n 2 +2, and R 3 go from 0 to 1. In the next pass R 2 goes to n 2 +4, and R 3 goes to 2. This continues until R 2 contains 2n 1 + n 2, and R 3 contains n 1. This will occur for any non-negative n 1 and n 2, so the function is total and we have f²(n 1, n 2 ) = 2n 1 + n 2. Finally, to work out the partial function f³ we assume initial input (n 1, n 2, n 3 ). We can see straight away that if n 3 > n 1 the program will never halt. Therefore the function is not defined for such values and cannot be a total function. If n 1 = n 3 the output will be n 2. And if n 1 > n 3 we will have R 2 going to n 2 +2(n 1 -n 3 ), and R 3 going to n 1. Therefore this function is not total and we have: f³(n 1, n 2, n 3 ) = n 2 +2(n 1 -n 3 ) for n 1 > n 3 ; f³(n 1, n 2, n 3 ) = n 2 for n 1 = n 3 ; f³(n 1, n 2, n 3 ) is undefined for n 1 < n EXAMPLE 2 The following URM program computes the function f(n) = n if n is odd, and f(n) = 0 if n is even: 1. J(1, 2, 8) 2. S(2) 3. J(1, 2, 8) 4. S(2) 5. J(1, 2, 7) 6. J(1, 1, 2) 7. Z(1) = 0 For example, the following is obtained with the input (3, 0): And the following is obtained with the input (4, 0):

6 EXAMPLE 3 The following URM program computes the function f(n, m) = n if n m, f(n, m) = m otherwise. In other words, it computes min(n, m). 1. J(1, 2, 7) 2. J(1, 3, 7) 3. J(2, 3, 6) 4. S(3) 5. J(1, 1, 2) 6. C(2, 1) For example, the following is obtained with the input (2, 3): And the following is obtained with the input (3, 2):

7 Note that to compute max(n, m), i.e., the function f(n, m) = n if n m, f(n, m) = m otherwise, it is only necessary to switch around the last digits in the Jump commands in lines 2 and 3, so the jump command in line 2 now goes to line 6, while the jump command in line 3 now goes to (non-existent) line 7. No other changes are needed EXAMPLE 4 The following URM program computes the function f(n, m) = nm. In other words, it carries out multiplication. 1. J(1, 4, 14) 2. J(2, 4, 13) 3. C(1, 3) 4. Z(1) 5. S(1) 6. S(4) 7. J(3, 4, 9) 8. J(1, 1, 5) 9. S(5) 10. J(2, 5, 14) 11. Z(4) 12. J(1, 1, 5) 13. Z(1) For example, the following is obtained with the input (2, 3):

8

(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

Lecture 13: Turing Machine

Lecture 13: Turing Machine Lecture 13: Turing Machine Instructor: Ketan Mulmuley Scriber: Yuan Li February 19, 2015 Turing machine is an abstract machine which in principle can simulate any computation in nature. Church-Turing Thesis:

More information

Lecture notes on Turing machines

Lecture notes on Turing machines Lecture notes on Turing machines Ivano Ciardelli 1 Introduction Turing machines, introduced by Alan Turing in 1936, are one of the earliest and perhaps the best known model of computation. The importance

More information

Turing Machines A Turing Machine is a 7-tuple, (Q, Σ, Γ, δ, q0, qaccept, qreject), where Q, Σ, Γ are all finite

Turing Machines A Turing Machine is a 7-tuple, (Q, Σ, Γ, δ, q0, qaccept, qreject), where Q, Σ, Γ are all finite The Church-Turing Thesis CS60001: Foundations of Computing Science Professor, Dept. of Computer Sc. & Engg., Turing Machines A Turing Machine is a 7-tuple, (Q, Σ, Γ, δ, q 0, q accept, q reject ), where

More information

Undecibability. Hilbert's 10th Problem: Give an algorithm that given a polynomial decides if the polynomial has integer roots or not.

Undecibability. Hilbert's 10th Problem: Give an algorithm that given a polynomial decides if the polynomial has integer roots or not. Undecibability Hilbert's 10th Problem: Give an algorithm that given a polynomial decides if the polynomial has integer roots or not. The problem was posed in 1900. In 1970 it was proved that there can

More information

Tape encoding of lists of numbers

Tape encoding of lists of numbers L7 74 We ve seen that a Turing machine s computation can be implemented by a register machine. The converse holds: the computation of a register machine can be implemented by a Turing machine. To make

More information

Lecture 14: Recursive Languages

Lecture 14: Recursive Languages Lecture 14: Recursive Languages Instructor: Ketan Mulmuley Scriber: Yuan Li February 24, 2015 1 Recursive Languages Definition 1.1. A language L Σ is called recursively enumerable (r. e.) or computably

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

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

Turing Machines Part Two

Turing Machines Part Two Turing Machines Part Two Recap from Last Time Our First Turing Machine q acc a start q 0 q 1 a This This is is the the Turing Turing machine s machine s finiteisttiteiconntont. finiteisttiteiconntont.

More information

ECE 695 Numerical Simulations Lecture 2: Computability and NPhardness. Prof. Peter Bermel January 11, 2017

ECE 695 Numerical Simulations Lecture 2: Computability and NPhardness. Prof. Peter Bermel January 11, 2017 ECE 695 Numerical Simulations Lecture 2: Computability and NPhardness Prof. Peter Bermel January 11, 2017 Outline Overview Definitions Computing Machines Church-Turing Thesis Polynomial Time (Class P)

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

Causes of Ineradicable Spurious Predictions in Qualitative Simulation

Causes of Ineradicable Spurious Predictions in Qualitative Simulation Causes of Ineradicable Spurious Predictions in Qualitative Simulation Özgür Y lmaz and A. C. Cem Say Bo aziçi University Department of Computer Engineering Bebek, 34342, stanbul, Turkey yilmozgu@boun.edu.tr,

More information

Recap DFA,NFA, DTM. Slides by Prof. Debasis Mitra, FIT.

Recap DFA,NFA, DTM. Slides by Prof. Debasis Mitra, FIT. Recap DFA,NFA, DTM Slides by Prof. Debasis Mitra, FIT. 1 Formal Language Finite set of alphabets Σ: e.g., {0, 1}, {a, b, c}, { {, } } Language L is a subset of strings on Σ, e.g., {00, 110, 01} a finite

More information

Register machines L2 18

Register machines L2 18 Register machines L2 18 Algorithms, informally L2 19 No precise definition of algorithm at the time Hilbert posed the Entscheidungsproblem, just examples. Common features of the examples: finite description

More information

Turing Machines Decidability

Turing Machines Decidability Turing Machines Decidability Master Informatique 2016 Some General Knowledge Alan Mathison Turing UK, 1912 1954 Mathematician, computer scientist, cryptanalyst Most famous works: Computation model («Turing

More information

Chapter 6: Turing Machines

Chapter 6: Turing Machines Chapter 6: Turing Machines 6.1 The Turing Machine Definition A deterministic Turing machine (DTM) M is specified by a sextuple (Q, Σ, Γ, δ, s, f), where Q is a finite set of states; Σ is an alphabet of

More information

CST Part IB. Computation Theory. Andrew Pitts

CST Part IB. Computation Theory. Andrew Pitts Computation Theory, L 1 1/171 CST Part IB Computation Theory Andrew Pitts Corrections to the notes and extra material available from the course web page: www.cl.cam.ac.uk/teaching/0910/comptheory/ Introduction

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

Introduction to Quantum Computing

Introduction to Quantum Computing Introduction to Quantum Computing The lecture notes were prepared according to Peter Shor s papers Quantum Computing and Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a

More information

CSCI 2200 Foundations of Computer Science Spring 2018 Quiz 3 (May 2, 2018) SOLUTIONS

CSCI 2200 Foundations of Computer Science Spring 2018 Quiz 3 (May 2, 2018) SOLUTIONS CSCI 2200 Foundations of Computer Science Spring 2018 Quiz 3 (May 2, 2018) SOLUTIONS 1. [6 POINTS] For language L 1 = {0 n 1 m n, m 1, m n}, which string is in L 1? ANSWER: 0001111 is in L 1 (with n =

More information

cse303 ELEMENTS OF THE THEORY OF COMPUTATION Professor Anita Wasilewska

cse303 ELEMENTS OF THE THEORY OF COMPUTATION Professor Anita Wasilewska cse303 ELEMENTS OF THE THEORY OF COMPUTATION Professor Anita Wasilewska LECTURE 13 CHAPTER 4 TURING MACHINES 1. The definition of Turing machine 2. Computing with Turing machines 3. Extensions of Turing

More information

6.8 The Post Correspondence Problem

6.8 The Post Correspondence Problem 6.8. THE POST CORRESPONDENCE PROBLEM 423 6.8 The Post Correspondence Problem The Post correspondence problem (due to Emil Post) is another undecidable problem that turns out to be a very helpful tool for

More information

Theory of Computer Science

Theory of Computer Science Theory of Computer Science D1. Turing-Computability Malte Helmert University of Basel April 18, 2016 Overview: Course contents of this course: logic How can knowledge be represented? How can reasoning

More information

CSE 2001: Introduction to Theory of Computation Fall Suprakash Datta

CSE 2001: Introduction to Theory of Computation Fall Suprakash Datta CSE 2001: Introduction to Theory of Computation Fall 2013 Suprakash Datta datta@cse.yorku.ca Office: CSEB 3043 Phone: 416-736-2100 ext 77875 Course page: http://www.cse.yorku.ca/course/2001 11/7/2013 CSE

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

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

CA320 - Computability & Complexity

CA320 - Computability & Complexity CA320 - Computability & Complexity David Sinclair Overview In this module we are going to answer 2 important questions: Can all problems be solved by a computer? What problems be efficiently solved by

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

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

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

Theory of Computation Lecture Notes. Problems and Algorithms. Class Information

Theory of Computation Lecture Notes. Problems and Algorithms. Class Information Theory of Computation Lecture Notes Prof. Yuh-Dauh Lyuu Dept. Computer Science & Information Engineering and Department of Finance National Taiwan University Problems and Algorithms c 2004 Prof. Yuh-Dauh

More information

COMPUTING THE BUSY BEAVER FUNCTION

COMPUTING THE BUSY BEAVER FUNCTION COMPUTING THE BUSY BEAVER FUNCTION In T. M. Cover and B. Gopinath, Open Problems in Communication and Computation, Springer, 1987, pp. 108 112 Gregory J. Chaitin IBM Research Division, P.O. Box 218 Yorktown

More information

CS 275 Automata and Formal Language Theory

CS 275 Automata and Formal Language Theory CS 275 Automata and Formal Language Theory Course Notes Part III: Limits of Computation Chapter III.1: Introduction Anton Setzer http://www.cs.swan.ac.uk/ csetzer/lectures/ automataformallanguage/current/index.html

More information

Models of Computation. by Costas Busch, LSU

Models of Computation. by Costas Busch, LSU Models of Computation by Costas Busch, LSU 1 Computation CPU memory 2 temporary memory input memory CPU output memory Program memory 3 Example: f ( x) x 3 temporary memory input memory Program memory compute

More information

ECS 120 Lesson 15 Turing Machines, Pt. 1

ECS 120 Lesson 15 Turing Machines, Pt. 1 ECS 120 Lesson 15 Turing Machines, Pt. 1 Oliver Kreylos Wednesday, May 2nd, 2001 Before we can start investigating the really interesting problems in theoretical computer science, we have to introduce

More information

Turing Machines (TM) The Turing machine is the ultimate model of computation.

Turing Machines (TM) The Turing machine is the ultimate model of computation. TURING MACHINES Turing Machines (TM) The Turing machine is the ultimate model of computation. Alan Turing (92 954), British mathematician/engineer and one of the most influential scientists of the last

More information

FINAL EXAM FOR PHIL 152 MICHAEL BEESON

FINAL EXAM FOR PHIL 152 MICHAEL BEESON FINAL EXAM FOR PHIL 152 MICHAEL BEESON Directions. This is an open-book, open-notes, open-homework. You can even search the Internet, but all the answers can be found in the lecture notes and homework

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

CSE 4111/5111/6111 Computability Jeff Edmonds Assignment 3: Diagonalization & Halting Problem Due: One week after shown in slides

CSE 4111/5111/6111 Computability Jeff Edmonds Assignment 3: Diagonalization & Halting Problem Due: One week after shown in slides CSE 4111/5111/6111 Computability Jeff Edmonds Assignment 3: Diagonalization & Halting Problem Due: One week after shown in slides First Person: Second Person: Family Name: Family Name: Given Name: Given

More information

AN INTRODUCTION TO COMPUTABILITY THEORY

AN INTRODUCTION TO COMPUTABILITY THEORY AN INTRODUCTION TO COMPUTABILITY THEORY CINDY CHUNG Abstract. This paper will give an introduction to the fundamentals of computability theory. Based on Robert Soare s textbook, The Art of Turing Computability:

More information

Introduction. Foundations of Computing Science. Pallab Dasgupta Professor, Dept. of Computer Sc & Engg INDIAN INSTITUTE OF TECHNOLOGY KHARAGPUR

Introduction. Foundations of Computing Science. Pallab Dasgupta Professor, Dept. of Computer Sc & Engg INDIAN INSTITUTE OF TECHNOLOGY KHARAGPUR 1 Introduction Foundations of Computing Science Pallab Dasgupta Professor, Dept. of Computer Sc & Engg 2 Comments on Alan Turing s Paper "On Computable Numbers, with an Application to the Entscheidungs

More information

Solutions to Homework Assignment 2

Solutions to Homework Assignment 2 Solutions to Homework Assignment Real Analysis I February, 03 Notes: (a) Be aware that there maybe some typos in the solutions. If you find any, please let me know. (b) As is usual in proofs, most problems

More information

Great Theoretical Ideas in Computer Science. Lecture 7: Introduction to Computational Complexity

Great Theoretical Ideas in Computer Science. Lecture 7: Introduction to Computational Complexity 15-251 Great Theoretical Ideas in Computer Science Lecture 7: Introduction to Computational Complexity September 20th, 2016 What have we done so far? What will we do next? What have we done so far? > Introduction

More information

Computation Theory, L 9 116/171

Computation Theory, L 9 116/171 Definition. A partial function f is partial recursive ( f PR) ifitcanbebuiltupinfinitelymanysteps from the basic functions by use of the operations of composition, primitive recursion and minimization.

More information

Well-Founded Iterations of Infinite Time Turing Machines

Well-Founded Iterations of Infinite Time Turing Machines Well-Founded of Infinite Time Turing Machines Robert S. Lubarsky Florida Atlantic University August 11, 2009 Useful for ordinal analysis Useful for ordinal analysis Iteration and hyper-iteration/feedback

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

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

Parallelism and Machine Models

Parallelism and Machine Models Parallelism and Machine Models Andrew D Smith University of New Brunswick, Fredericton Faculty of Computer Science Overview Part 1: The Parallel Computation Thesis Part 2: Parallelism of Arithmetic RAMs

More information

Decidability. Linz 6 th, Chapter 12: Limits of Algorithmic Computation, page 309ff

Decidability. Linz 6 th, Chapter 12: Limits of Algorithmic Computation, page 309ff Decidability Linz 6 th, Chapter 12: Limits of Algorithmic Computation, page 309ff 1 A property P of strings is said to be decidable if the set of all strings having property P is a recursive set; that

More information

15 th Annual Harvard-MIT Mathematics Tournament Saturday 11 February 2012

15 th Annual Harvard-MIT Mathematics Tournament Saturday 11 February 2012 1 th Annual Harvard-MIT Mathematics Tournament Saturday 11 February 01 1. Let f be the function such that f(x) = { x if x 1 x if x > 1 What is the total length of the graph of f(f(...f(x)...)) from x =

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

Undecidability. We are not so much concerned if you are slow as when you come to a halt. (Chinese Proverb)

Undecidability. We are not so much concerned if you are slow as when you come to a halt. (Chinese Proverb) We are not so much concerned if you are slow as when you come to a halt. (Chinese Proverb) CS /55 Theory of Computation The is A TM = { M,w M is a TM and w L(M)} A TM is Turing-recognizable. Proof Sketch:

More information

CSCC63 Worksheet Turing Machines

CSCC63 Worksheet Turing Machines 1 An Example CSCC63 Worksheet Turing Machines Goal. Design a turing machine, M that accepts only strings of the form {w#w w {0, 1} }. Idea. Describe in words how the machine would work. Read first symbol

More information

ON COMPUTAMBLE NUMBERS, WITH AN APPLICATION TO THE ENTSCHENIDUGSPROBLEM. Turing 1936

ON COMPUTAMBLE NUMBERS, WITH AN APPLICATION TO THE ENTSCHENIDUGSPROBLEM. Turing 1936 ON COMPUTAMBLE NUMBERS, WITH AN APPLICATION TO THE ENTSCHENIDUGSPROBLEM Turing 1936 Where are We? Ignoramus et ignorabimus Wir mussen wissen Wir werden wissen We do not know We shall not know We must know

More information

Lecture 13: Foundations of Math and Kolmogorov Complexity

Lecture 13: Foundations of Math and Kolmogorov Complexity 6.045 Lecture 13: Foundations of Math and Kolmogorov Complexity 1 Self-Reference and the Recursion Theorem 2 Lemma: There is a computable function q : Σ* Σ* such that for every string w, q(w) is the description

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 12: Turing Machines Turing Machines I After having dealt with partial recursive functions,

More information

CSE 2001: Introduction to Theory of Computation Fall Suprakash Datta

CSE 2001: Introduction to Theory of Computation Fall Suprakash Datta CSE 2001: Introduction to Theory of Computation Fall 2012 Suprakash Datta datta@cse.yorku.ca Office: CSEB 3043 Phone: 416-736-2100 ext 77875 Course page: http://www.cs.yorku.ca/course/2001 11/13/2012 CSE

More information

α-recursion Theory and Ordinal Computability

α-recursion Theory and Ordinal Computability α-recursion Theory and Ordinal Computability by Peter Koepke University of Bonn 1 3. 2. 2007 Abstract Motivated by a talk of S. D. Friedman at BIWOC we show that the α-recursive and α-recursively enumerable

More information

The P versus NP Problem. Dean Casalena University of Cape Town CSLDEA001

The P versus NP Problem. Dean Casalena University of Cape Town CSLDEA001 The P versus NP Problem Dean Casalena University of Cape Town CSLDEA001 dean@casalena.co.za Contents 1. Introduction 2. Turing Machines and Syntax 2.1 Overview 2.2 Turing Machine Syntax. 2.3 Polynomial

More information

Midterm II : Formal Languages, Automata, and Computability

Midterm II : Formal Languages, Automata, and Computability Midterm II 15-453: Formal Languages, Automata, and Computability Lenore Blum, Asa Frank, Aashish Jindia, and Andrew Smith April 8, 2014 Instructions: 1. Once the exam begins, write your name on each sheet.

More information

Q = Set of states, IE661: Scheduling Theory (Fall 2003) Primer to Complexity Theory Satyaki Ghosh Dastidar

Q = Set of states, IE661: Scheduling Theory (Fall 2003) Primer to Complexity Theory Satyaki Ghosh Dastidar IE661: Scheduling Theory (Fall 2003) Primer to Complexity Theory Satyaki Ghosh Dastidar Turing Machine A Turing machine is an abstract representation of a computing device. It consists of a read/write

More information

Turing 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? 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 information

Turing Machines. 22c:135 Theory of Computation. Tape of a Turing Machine (TM) TM versus FA, PDA

Turing Machines. 22c:135 Theory of Computation. Tape of a Turing Machine (TM) TM versus FA, PDA Turing Machines A Turing machine is similar to a finite automaton with supply of unlimited memory. A Turing machine can do everything that any computing device can do. There exist problems that even a

More information

ENEE 459E/CMSC 498R In-class exercise February 10, 2015

ENEE 459E/CMSC 498R In-class exercise February 10, 2015 ENEE 459E/CMSC 498R In-class exercise February 10, 2015 In this in-class exercise, we will explore what it means for a problem to be intractable (i.e. it cannot be solved by an efficient algorithm). There

More information

Predicate Logic - Undecidability

Predicate Logic - Undecidability CS402, Spring 2016 Undecidable Problems Does the following program halts? (1) N : n, total, x, y, z (2) n GetUserInput() (3) total 3 (4) while true (5) for x 1 to total 2 (6) for y 1 to total x 1 (7) z

More information

258 Handbook of Discrete and Combinatorial Mathematics

258 Handbook of Discrete and Combinatorial Mathematics 258 Handbook of Discrete and Combinatorial Mathematics 16.3 COMPUTABILITY Most of the material presented here is presented in far more detail in the texts of Rogers [R], Odifreddi [O], and Soare [S]. In

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

VI. Church-Turing Thesis

VI. Church-Turing Thesis VI. Church-Turing Thesis Yuxi Fu BASICS, Shanghai Jiao Tong University Fundamental Question How do computation models characterize the informal notion of effective computability? Computability Theory,

More information

Theory of Computation

Theory of Computation Theory of Computation Prof. Michael Mascagni Florida State University Department of Computer Science 1 / 33 This course aims to cover... the development of computability theory using an extremely simple

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

CMPSCI 250: Introduction to Computation. Lecture #15: The Fundamental Theorem of Arithmetic David Mix Barrington 24 February 2014

CMPSCI 250: Introduction to Computation. Lecture #15: The Fundamental Theorem of Arithmetic David Mix Barrington 24 February 2014 CMPSCI 250: Introduction to Computation Lecture #15: The Fundamental Theorem of Arithmetic David Mix Barrington 24 February 2014 The Fundamental Theorem Statement of the Theorem Existence of a Factorization

More information

Intro to Theory of Computation

Intro to Theory of Computation Intro to Theory of Computation LECTURE 22 Last time Review Today: Finish recursion theorem Complexity theory Exam 2 solutions out Homework 9 out Sofya Raskhodnikova L22.1 I-clicker question (frequency:

More information

Ordinal Computability

Ordinal Computability Ordinal Computability by Peter Koepke University of Bonn EMU - Effective Mathematics of the Uncountable CUNY Graduate Center, August 8, 2008 1 A standard Turing computation n 0 0 0 0 0 1 n + 1 0 0 0 0

More information

CS154, Lecture 12: Kolmogorov Complexity: A Universal Theory of Data Compression

CS154, Lecture 12: Kolmogorov Complexity: A Universal Theory of Data Compression CS154, Lecture 12: Kolmogorov Complexity: A Universal Theory of Data Compression Rosencrantz & Guildenstern Are Dead (Tom Stoppard) Rigged Lottery? And the winning numbers are: 1, 2, 3, 4, 5, 6 But is

More information

Chapter-2 Relations and Functions. Miscellaneous

Chapter-2 Relations and Functions. Miscellaneous 1 Chapter-2 Relations and Functions Miscellaneous Question 1: The relation f is defined by The relation g is defined by Show that f is a function and g is not a function. The relation f is defined as It

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

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

Models of Computation, Recall Register Machines. A register machine (sometimes abbreviated to RM) is specified by:

Models of Computation, Recall Register Machines. A register machine (sometimes abbreviated to RM) is specified by: Models of Computation, 2010 1 Definition Recall Register Machines A register machine (sometimes abbreviated M) is specified by: Slide 1 finitely many registers R 0, R 1,..., R n, each capable of storing

More information

Please give details of your answer. A direct answer without explanation is not counted.

Please give details of your answer. A direct answer without explanation is not counted. Please give details of your answer. A direct answer without explanation is not counted. Your answers must be in English. Please carefully read problem statements. During the exam you are not allowed to

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

Math 324 Summer 2012 Elementary Number Theory Notes on Mathematical Induction

Math 324 Summer 2012 Elementary Number Theory Notes on Mathematical Induction Math 4 Summer 01 Elementary Number Theory Notes on Mathematical Induction Principle of Mathematical Induction Recall the following axiom for the set of integers. Well-Ordering Axiom for the Integers If

More information

Great Theoretical Ideas in Computer Science. Lecture 9: Introduction to Computational Complexity

Great Theoretical Ideas in Computer Science. Lecture 9: Introduction to Computational Complexity 15-251 Great Theoretical Ideas in Computer Science Lecture 9: Introduction to Computational Complexity February 14th, 2017 Poll What is the running time of this algorithm? Choose the tightest bound. def

More information

Opleiding Informatica

Opleiding 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 information

Lecture 14 Rosser s Theorem, the length of proofs, Robinson s Arithmetic, and Church s theorem. Michael Beeson

Lecture 14 Rosser s Theorem, the length of proofs, Robinson s Arithmetic, and Church s theorem. Michael Beeson Lecture 14 Rosser s Theorem, the length of proofs, Robinson s Arithmetic, and Church s theorem Michael Beeson The hypotheses needed to prove incompleteness The question immediate arises whether the incompleteness

More information

X-machines - a computational model framework.

X-machines - a computational model framework. Chapter 2. X-machines - a computational model framework. This chapter has three aims: To examine the main existing computational models and assess their computational power. To present the X-machines as

More information

Chapter 8. Turing Machine (TMs)

Chapter 8. Turing Machine (TMs) Chapter 8 Turing Machine (TMs) Turing Machines (TMs) Accepts the languages that can be generated by unrestricted (phrase-structured) grammars No computational machine (i.e., computational language recognition

More information

Complexity Theory Part I

Complexity Theory Part I Complexity Theory Part I Problem Problem Set Set 77 due due right right now now using using a late late period period The Limits of Computability EQ TM EQ TM co-re R RE L D ADD L D HALT A TM HALT A TM

More information

Automata Theory (2A) Young Won Lim 5/31/18

Automata Theory (2A) Young Won Lim 5/31/18 Automata Theory (2A) Copyright (c) 2018 Young W. Lim. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later

More information

CSE 105 THEORY OF COMPUTATION

CSE 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 4.1 Explain what it means for a problem to be decidable. Justify the use

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

CS 275 Automata and Formal Language Theory

CS 275 Automata and Formal Language Theory CS 275 Automata and Formal Language Theory Course Notes Part III: Limits of Computation Chapt. III.1: Introduction Anton Setzer http://www.cs.swan.ac.uk/ csetzer/lectures/ automataformallanguage/current/index.html

More information

Infinite Time Register Machines

Infinite Time Register Machines Infinite Time Register Machines Peter Koepke University of Bonn Mathematisches Institut Beringstraße D 535 Bonn Germany Koepke@Math.Uni-Bonn.de Abstract. Infinite time register machines (ITRMs) are register

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

On some Metatheorems about FOL

On some Metatheorems about FOL On some Metatheorems about FOL February 25, 2014 Here I sketch a number of results and their proofs as a kind of abstract of the same items that are scattered in chapters 5 and 6 in the textbook. You notice

More information

CS21 Decidability and Tractability

CS21 Decidability and Tractability CS21 Decidability and Tractability Lecture 14 February 7, 2018 February 7, 2018 CS21 Lecture 14 1 Outline Gödel Incompleteness Theorem February 7, 2018 CS21 Lecture 14 2 Background Hilbert s program (1920

More information

Complexity Theory Part II

Complexity Theory Part II Complexity Theory Part II Time Complexity The time complexity of a TM M is a function denoting the worst-case number of steps M takes on any input of length n. By convention, n denotes the length of the

More information

Theory of Computation

Theory of Computation Theory of Computation Lecture #6 Sarmad Abbasi Virtual University Sarmad Abbasi (Virtual University) Theory of Computation 1 / 39 Lecture 6: Overview Prove the equivalence of enumerators and TMs. Dovetailing

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

Self-reference in computability theory and the universal algorithm

Self-reference in computability theory and the universal algorithm Self-reference in computability theory and the universal algorithm Joel David Hamkins City University of New York CUNY Graduate Center Mathematics, Philosophy, Computer Science College of Staten Island

More information