Applied Computer Science II Chapter 3 : Turing Machines Prof. Dr. Luc De Raedt Institut für Informatik Albert-Ludwigs Universität Freiburg Germany.

Slides:



Advertisements
Similar presentations
Algorithms Sipser 3.3 (pages ). CS 311 Fall Computability Hilbert's Tenth Problem: Find a process according to which it can be determined.
Advertisements

Turing Machines Memory = an infinitely long tape Persistent storage A read/write tape head that can move around the tape Initially, the tape contains only.
Applied Computer Science II Chapter 4: Decidability Prof. Dr. Luc De Raedt Institut für Informatik Albert-Ludwigs Universität Freiburg Germany.
CS 345: Chapter 9 Algorithmic Universality and Its Robustness
Recap CS605: The Mathematics and Theory of Computer Science.
Foundations of (Theoretical) Computer Science Chapter 3 Lecture Notes (Section 3.2: Variants of Turing Machines) David Martin With.
Turing Machines (At last!). Designing Universal Computational Devices Was Not The Only Contribution from Alan Turing… Enter the year 1940: The world is.
CS605 – The Mathematics and Theory of Computer Science Turing Machines.
Applied Computer Science II Chapter 1 : Regular Languages Prof. Dr. Luc De Raedt Institut für Informatik Albert-Ludwigs Universität Freiburg Germany.
Algorithms Sipser 3.3 (pages ). CS 311 Mount Holyoke College 2 Computability Hilbert's Tenth Problem: Find “a process according to which it can.
More Turing Machines Sipser 3.2 (pages ). CS 311 Fall Multitape Turing Machines Formally, we need only change the transition function to.
1 Introduction to Computability Theory Lecture11: Variants of Turing Machines Prof. Amos Israeli.
More Turing Machines Sipser 3.2 (pages ).
Applied Computer Science II Chapter 2 : Context-free languages Prof. Dr. Luc De Raedt Institut für Informatik Albert-Ludwigs Universität Freiburg Germany.
CS5371 Theory of Computation Lecture 11: Computability Theory II (TM Variants, Church-Turing Thesis)
1 Turing Machines. 2 The Language Hierarchy Regular Languages Context-Free Languages ? ?
Programming the TM qa  (,q) (,q) q1q1 0q1q1 R q1q1 1q1q1 R q1q1  h  Qa  (,q) (,q) q1q1 0q2q2  q1q1 1q3q3  q1q1  h  q2q2 0q4q4 R q2q2 1q4q4.
Lecture 5 Turing Machines
Computation Theory Introduction to Turing Machine.
Turing Machines.
CHAPTER 3 The Church-Turing Thesis
Applied Computer Science II Chapter 5: Reducability Prof. Dr. Luc De Raedt Institut für Informatik Albert-Ludwigs Universität Freiburg Germany.
Foundations of (Theoretical) Computer Science
Applied Computer Science II Chapter 7: Time Complexity Prof. Dr. Luc De Raedt Institut für Informatik Albert-Ludwigs Universität Freiburg Germany.
CS5371 Theory of Computation Lecture 10: Computability Theory I (Turing Machine)
January 28, 2015CS21 Lecture 101 CS21 Decidability and Tractability Lecture 10 January 28, 2015.
Prof. Busch - LSU1 Turing Machines. Prof. Busch - LSU2 The Language Hierarchy Regular Languages Context-Free Languages ? ?
INHERENT LIMITATIONS OF COMPUTER PROGRAMS CSci 4011.
Turing Machines A more powerful computation model than a PDA ?
Complexity theory and combinatorial optimization Class #2 – 17 th of March …. where we deal with decision problems, finite automata, Turing machines pink.
Introduction to CS Theory Lecture 15 –Turing Machines Piotr Faliszewski
Turing Machines – Decidability Lecture 25 Section 3.1 Fri, Oct 19, 2007.
Turing Machines. Intro to Turing Machines A Turing Machine (TM) has finite-state control (like PDA), and an infinite read-write tape. The tape serves.
Computability Chapter 5. Overview  Turing Machine (TM) considered to be the most general computational model that can be devised (Church-Turing thesis)
1Computer Sciences Department. Book: INTRODUCTION TO THE THEORY OF COMPUTATION, SECOND EDITION, by: MICHAEL SIPSER Reference 3Computer Sciences Department.
Automata & Formal Languages, Feodor F. Dragan, Kent State University 1 CHAPTER 3 The Church-Turing Thesis Contents Turing Machines definitions, examples,
CSC 3130: Automata theory and formal languages Andrej Bogdanov The Chinese University of Hong Kong Turing Machines.
Turing -Recognizable vs. -Decidable
Donghyun (David) Kim Department of Mathematics and Computer Science North Carolina Central University 1 Chapter 3 Church-Turing Thesis Some slides are.
CS 208: Computing Theory Assoc. Prof. Dr. Brahim Hnich
Capabilities of computing systems Numeric and symbolic Computations A look at Computability theory Turing Machines.
Overview of the theory of computation Episode 3 0 Turing machines The traditional concepts of computability, decidability and recursive enumerability.
Automata & Formal Languages, Feodor F. Dragan, Kent State University 1 CHAPTER 3 The Church-Turing Thesis Contents Turing Machines definitions, examples,
 2004 SDU 1 Algorithm Informally speaking, an algorithm is a collection of simple instructions for carrying out a task. Example:  Elementary arithmetic.
1 Introduction to Turing Machines
1 CD5560 FABER Formal Languages, Automata and Models of Computation Lecture 12 Mälardalen University 2007.
Umans Complexity Theory Lectures Lecture 1b: Turing Machines & Halting Problem.
Donghyun (David) Kim Department of Mathematics and Computer Science North Carolina Central University 1 Chapter 5 Reducibility Some slides are in courtesy.
The Church-Turing Thesis
1 Turing Machines. 2 The Language Hierarchy Regular Languages Context-Free Languages ? ?
The Church-Turing Thesis Chapter Are We Done? FSM  PDA  Turing machine Is this the end of the line? There are still problems we cannot solve:
Theory of Computational Complexity TA : Junichi Teruyama Iwama lab. D3
Chapters 11 and 12 Decision Problems and Undecidability.
Modeling Arithmetic, Computation, and Languages Mathematical Structures for Computer Science Chapter 8 Copyright © 2006 W.H. Freeman & Co.MSCS SlidesTuring.
Turing’s Thesis.
Turing’s Thesis Costas Busch - LSU.
Busch Complexity Lectures: Turing Machines
CS21 Decidability and Tractability
CSE 105 theory of computation
CSE 105 theory of computation
Chapter 3: The CHURCH-Turing thesis
فصل سوم The Church-Turing Thesis
Intro to Theory of Computation
Decidable Languages Costas Busch - LSU.
Chapter 3 Turing Machines.
CS21 Decidability and Tractability
Decidability and Tractability
CSE 105 theory of computation
CSE 105 theory of computation
Presentation transcript:

Applied Computer Science II Chapter 3 : Turing Machines Prof. Dr. Luc De Raedt Institut für Informatik Albert-Ludwigs Universität Freiburg Germany

Overview Turing machines Variants of Turing machines –Multi-tape –Non-deterministic –… The definition of algorithm –The Church-Turing Thesis

Turing Machine Infinite tape –Both read and write from tape –Move left and right –Special accept and reject state take immediate effect –Machine can accept, reject or loop

Turing Machines

Configurations

Languages The collection of strings that M accepts is the language of M, L(M) A language is Turing-recognizable (recursively enumerable) if some Turing machine accepts it Deciders halt on every input (i.e. they do not loop) A language is Turing-decidable (recursive) if some Turing machine decides it

Variants of Turing Machines Most of them turn out to be equivalent to original model E.g. consider movements of head on tape {L,R,S} where S denotes “same” Equivalent to original model (represent S transition by first R and then L, or vice versa)

Multi-tape Turing Machines

Non-deterministic TMs

Insert p 139

Enumerators

Insert theorem 3.13

Equivalence with other models Many variants of TMs (and related constructs) exist. All of them turn out to be equivalent in power (under reasonable assumptions, such as finite amount of work in single step) Programming languages : Lisp, Haskell, Pascal, Java, C, … The class of algorithms described is natural and identical for all these constructs. For a given task, one type of construct may be more elegant.

The definition of an algorithm David Hilbert –Paris, 1900, Intern. Congress of Maths. –23 mathematical problems formulated 10 th problem –“to devise an algorithm that tests whether a polynomial has an integral root” –Algorithm = “a process according to which it can be determined by a finite number of operations”

Integral roots of polynomials There is no algorithm that solves this task. A formal notion of algorithm is necessary. Alonso Church : -calculus (cf. functional programming) Allen Turing : Turing machines

Integral roots of polynomials There is no algorithm that solves this task. A formal notion of algorithm is necessary. Alonso Church : -calculus (cf. functional programming) Allen Turing : Turing machines

Turing machines Three levels of description –Formal description –Implementation level –High-level description The algorithm is described From now on, we use this level of description

Connected graphs

Overview Turing machines Variants of Turing machines –Multi-tape –Non-deterministic –… The definition of algorithm –The Church-Turing Thesis