"튜링 기계"의 두 판 사이의 차이

수학노트
둘러보기로 가기 검색하러 가기
imported>Pythagoras0
 
(사용자 2명의 중간 판 6개는 보이지 않습니다)
8번째 줄: 8번째 줄:
 
* Palindrome cheker
 
* Palindrome cheker
 
* Binary addition
 
* Binary addition
 +
 +
 +
==unary double==
 +
* x,1,a,R,y
 +
* x,b,1,R,x
 +
* x, , ,R,HALT
 +
* y,1,1,R,y
 +
* y,b,b,R,y
 +
* y, ,b,L,z
 +
* z,1,1,L,z
 +
* z,b,b,L,z
 +
* z,a,1,R,x
 +
 +
==computational resource==
 +
* http://www.python-course.eu/turing_machine.php
 +
 +
 +
== 노트 ==
 +
 +
* A probabilistic Turing machine (PTM) is a Turing machine (TM) modified for executing a randomized computation.<ref name="ref_ac20">[https://encyclopediaofmath.org/wiki/Probabilistic_Turing_machine Probabilistic Turing machine]</ref>
 +
* Essentially, a Turing machine consists of a tape with instructions written on it and the device that can read up and down the tape.<ref name="ref_926c">[https://blog.talla.com/neural-turing-machines-perils-and-promise Neural Turing Machines: Perils and Promise]</ref>
 +
* Neural Turing Machines have taken all of the functions of the basic Turing machine and found smooth analogues.<ref name="ref_926c" />
 +
* All a Turing machine does is read and write from a piece of tape.<ref name="ref_e7d0">[https://medium.com/background-thread/whats-a-turing-machine-and-why-does-it-matter-1cd1b4606c6a What’s a Turing Machine? (And Why Does It Matter?)]</ref>
 +
* A much better way to write a Turing machine is with a diagram like above.<ref name="ref_e7d0" />
 +
* We define the symbols a Turing machine works with.<ref name="ref_e7d0" />
 +
* In other words, any algorithm ever can be built on a Turing machine.<ref name="ref_e7d0" />
 +
* A Turing machine is a hypothetical machine thought up by Alan Turing.<ref name="ref_fd2a">[https://becominghuman.ai/we-are-all-turing-machines-ad82c3dd9e50 We are all Turing machines.]</ref>
 +
* Conceptually, the Turing machine consists of an infinite tape and a tape head.<ref name="ref_fd2a" />
 +
* We can simulate Turing machines (with finite tape) on our computers, but they are notoriously cumbersome to program.<ref name="ref_fd2a" />
 +
* The machines discussed in this article are not the same as the hypothetical Turing machine as Alan Turing defined it.<ref name="ref_fd2a" />
 +
* Section 2 provides some basic notations about Turing machine, Rubel’s EAC model, and the uEAC.<ref name="ref_65e8">[https://www.hindawi.com/journals/mpe/2015/236806/ Simulation of Turing Machine with uEAC-Computable Functions]</ref>
 +
* A Turing machine can be seen as a state machine; at each moment the machine is in one of a finite number of states.<ref name="ref_65e8" />
 +
* Consider an example of single tape Turing machine with three states and is the initial state.<ref name="ref_65e8" />
 +
* In Figure 1, states of the Turing machine are represented by circles, with the concentric circle being the initial state .<ref name="ref_65e8" />
 +
* We will begin by constructing a Turing machine for the language L = {anbncn}.<ref name="ref_a6ba">[http://www.jflap.com/tutorial/turing/one/index.html Turing Machine]</ref>
 +
* We will be adding a lot of states to create a Turing machine for L = {anbncn}.<ref name="ref_a6ba" />
 +
* The value in the first box represents the current value under the head of the Turing machine.<ref name="ref_a6ba" />
 +
* Add the transitions in your screen below to your Turing machine.<ref name="ref_a6ba" />
 +
* It was late one night when I was starting my problem set on writing a turing machine to compute some operation.<ref name="ref_0c53">[https://web.mit.edu/manoli/turing/www/turing.html Universal Turing Machine]</ref>
 +
* *position* position)) ;; The following are the procedures that implement the Turing machine.<ref name="ref_0c53" />
 +
* A turing machine consists of a tape of infinite length on which read and writes operation can be performed.<ref name="ref_f9f4">[https://www.geeksforgeeks.org/turing-machine-in-toc/ Turing Machine in TOC]</ref>
 +
* Below, you can see the initial configuration of a Turing machine on the input 101001: .<ref name="ref_891a">[http://www.logique.jussieu.fr/~michel/tmi.html Turing machines]</ref>
 +
* In 1936, Turing defined Turing machines as a universal model of computation on natural numbers.<ref name="ref_891a" />
 +
* This means that all computable functions you can imagine can be computed by a Turing machine.<ref name="ref_891a" />
 +
* He considered Turing machines with 2 symbols, and defined the functions S(n,2) and Sigma(n,2).<ref name="ref_891a" />
 +
* A Turing machine consists of a line of cells known as the "tape", together with a single active cell, known as the "head".<ref name="ref_64b6">[https://www.wolframscience.com/prizes/tm23/turingmachine.html Wolfram 2,3 Turing Machine Research Prize : What is a Turing Machine?]</ref>
 +
* Any particular Turing machine is defined by a rule which specifies what the head should do at each step.<ref name="ref_64b6" />
 +
* Not every Turing machine has this property; many can only behave in very simple ways.<ref name="ref_64b6" />
 +
* A universal Turing machine has the property that it can emulate any other Turing machine---or indeed any computer or software system.<ref name="ref_64b6" />
 +
* Then run the instructions two more times and see if you can figure out what this Turing machine does.<ref name="ref_ffa6">[https://www.futurelearn.com/info/courses/how-computers-work/0/steps/49259 Turing machines]</ref>
 +
* So this Turing machine is designed to flip bits.<ref name="ref_ffa6" />
 +
* The instructions for this Turing machine only had one state, but more complex Turing machines can be built using multiple states.<ref name="ref_ffa6" />
 +
* In this step, we’re going to have a look at Turing machines, which were hypothetical computers invented by Alan Turing in 1936.<ref name="ref_ffa6" />
 +
* next → ← prev Turing Machine Turing machine was invented in 1936 by Alan Turing.<ref name="ref_036a">[https://www.javatpoint.com/automata-turing-machine Automata Turing Machine]</ref>
 +
* There are various features of the Turing machine: It has an external memory which remembers arbitrary long sequence of input.<ref name="ref_036a" />
 +
* Thus a common set of alphabets can be used for the Turing machine.<ref name="ref_036a" />
 +
* The main advantage of the Turing machine is we have a tape head which can be moved forward or backward, and the input tape can be scanned.<ref name="ref_036a" />
 +
* In its simplest form, a Turing machine is composed of a "tape", a ribbon of paper of indefinite length.<ref name="ref_6d9d">[http://www.mapageweb.umontreal.ca/cousined/lego/5-machines/turing/turing.html Turing machine]</ref>
 +
* The Turing machine is said to be in a certain "state".<ref name="ref_6d9d" />
 +
* We then say a Turing machine is emulating another one (the one on the tape).<ref name="ref_6d9d" />
 +
* the same computational capabilities than a Turing machine is to see if it can emulate a Turing machine.<ref name="ref_6d9d" />
 +
* A Turing machine is an abstract computational device that can be in one of a finite set of possible states.<ref name="ref_8d09">[https://www.sciencedirect.com/topics/physics-and-astronomy/turing-machines Turing Machines - an overview]</ref>
 +
* The computational complexity of an algorithm is measured by the number of steps required by a Turing machine to run through the algorithm.<ref name="ref_8d09" />
 +
* A Turing machine as defined above is a deterministic machine.<ref name="ref_8d09" />
 +
* For each sequence of choices, the sequence of transitions corresponds to a sequence of steps executed by a deterministic Turing machine.<ref name="ref_8d09" />
 +
* To show there were algorithms that Turing machines would run indefinitely and inconclusively was a way of showing Hilbert was mistaken.<ref name="ref_de21">[https://www.newscientist.com/article/mg23130803-200-how-alan-turing-found-machine-thinking-in-the-human-mind/ How Alan Turing found machine thinking in the human mind]</ref>
 +
* , Turing noted that people are really Turing machines.<ref name="ref_de21" />
 +
* A Turing machine is a very simple machine, but, logically speaking, has all the power of any digital computer.<ref name="ref_9fef">[http://www.ams.org/publicoutreach/feature-column/fcarc-turing AMS :: Feature Column from the AMS]</ref>
 +
* A Turing machine processes an infinite tape.<ref name="ref_9fef" />
 +
* At any time, the Turing machine has a read/write head positioned at some square on the tape.<ref name="ref_9fef" />
 +
* The very simplicity of a Turing machine makes it a challenge to program one to perform a specific computation.<ref name="ref_9fef" />
 +
* As shown in the animation above, a Turing machine consists of a tape that is initialized with a string of symbols.<ref name="ref_7565">[https://brilliant.org/wiki/turing-machines/ Brilliant Math & Science Wiki]</ref>
 +
* The table below describes a simple Turing machine that takes a string of 1 1 1’s as input and doubles it.<ref name="ref_7565" />
 +
* A state register stores the state of the Turing machine.<ref name="ref_021c">[https://www.tutorialspoint.com/automata_theory/turing_machine_introduction.htm Turing Machine Introduction]</ref>
 +
* The heart of the turing machine is the read-write head.<ref name="ref_c362">[http://aturingmachine.com/ A Turing Machine Overview]</ref>
 +
* As Turing claimed, any process that can be naturally called an effective procedure is realized by a Turing machine.<ref name="ref_c84a">[http://www.scholarpedia.org/article/Turing_machine Turing machine]</ref>
 +
* If the Turing machine halts for all inputs, then the function computed is defined for all arguments and we call it total computable.<ref name="ref_c84a" />
 +
* It is possible to give an effective (computable) one-to-one pairing between natural numbers and Turing machines.<ref name="ref_c84a" />
 +
* The last reference contains an excellent discussion of Turing machines, their computations, and related machines.<ref name="ref_c84a" />
 +
* Turing completeness is the ability for a system of instructions to simulate a Turing machine.<ref name="ref_8d5e">[https://en.wikipedia.org/wiki/Turing_machine Turing machine]</ref>
 +
* The Turing machine mathematically models a machine that mechanically operates on a tape.<ref name="ref_8d5e" />
 +
* A state register that stores the state of the Turing machine, one of finitely many.<ref name="ref_8d5e" />
 +
* that stores the state of the Turing machine, one of finitely many.<ref name="ref_8d5e" />
 +
* There are just six types of fundamental operation that a Turing machine performs in the course of a computation.<ref name="ref_c686">[http://www.alanturing.net/turing_archive/pages/Reference%20Articles/What%20is%20a%20Turing%20Machine.html AlanTuring.net What is a Turing machine?]</ref>
 +
* It is a remarkable fact that none of these computers can outdo a Turing machine.<ref name="ref_c686" />
 +
* Despite the Turing machine's austere simplicity, it is capable of computing anything that any computer on the market can compute.<ref name="ref_c686" />
 +
* Indeed, since it is an abstract or notional machine, a Turing machine can compute more than any physical computer.<ref name="ref_c686" />
 +
* They were first named ‘Turing machines’ by Alonzo Church in a review of Turing’s paper (Church 1937).<ref name="ref_accc">[https://plato.stanford.edu/entries/turing-machine/ Turing Machines (Stanford Encyclopedia of Philosophy)]</ref>
 +
* Turing introduced Turing machines in the context of research into the foundations of mathematics.<ref name="ref_accc" />
 +
* Another typical format to represent Turing machines and which was also used by Turing is the transition table.<ref name="ref_accc" />
 +
* Thus, Post introduced a modified version of the Turing machine.<ref name="ref_accc" />
 +
* A template for specifying a 3-state, 2-color Turing machine is shown above using a form of notation due to Wolfram (2002).<ref name="ref_a9e3">[https://mathworld.wolfram.com/TuringMachine.html Turing Machine -- from Wolfram MathWorld]</ref>
 +
* An example 3-state, 2-color Turing machine is illustrated above (Wolfram 2002, p. 78).<ref name="ref_a9e3" />
 +
* Determining whether a Turing machine will ever halt for a given input and set of rules is called the halting problem.<ref name="ref_a9e3" />
 +
* For an -state binary Turing machine, the number of 1s written for a busy beaver is denoted .<ref name="ref_a9e3" />
 +
* In section two, let's learn about LEDs, GPIO pins, resistors, and python, before embarking on building our Turing machine!<ref name="ref_a14c">[https://www.cl.cam.ac.uk/projects/raspberrypi/tutorials/turing-machine/one.html Department of Computer Science and Technology – Raspberry Pi: Introduction: What is a Turing machine?]</ref>
 +
===소스===
 +
<references />
 +
 +
==메타데이터==
 +
===위키데이터===
 +
* ID :  [https://www.wikidata.org/wiki/Q163310 Q163310]
 +
===Spacy 패턴 목록===
 +
* [{'LOWER': 'turing'}, {'LEMMA': 'machine'}]
 +
* [{'LOWER': 'deterministic'}, {'LOWER': 'turing'}, {'LEMMA': 'machine'}]

2021년 2월 17일 (수) 03:16 기준 최신판

example

  • http://www.soc.napier.ac.uk/~andrew/tm/ryo.htm
  • Unary increment - this function takes a string of 1's and adds another: 111→1111
  • Unary decrement - this function takes a string of 1's and removes one: 111→11
  • Binary double - this function doubles a binary string: 111→1110
  • Binary increment - add one to a binary number: 101→110
  • Unary double - double the length of a unary string 111→111111
  • Palindrome cheker
  • Binary addition


unary double

  • x,1,a,R,y
  • x,b,1,R,x
  • x, , ,R,HALT
  • y,1,1,R,y
  • y,b,b,R,y
  • y, ,b,L,z
  • z,1,1,L,z
  • z,b,b,L,z
  • z,a,1,R,x

computational resource


노트

  • A probabilistic Turing machine (PTM) is a Turing machine (TM) modified for executing a randomized computation.[1]
  • Essentially, a Turing machine consists of a tape with instructions written on it and the device that can read up and down the tape.[2]
  • Neural Turing Machines have taken all of the functions of the basic Turing machine and found smooth analogues.[2]
  • All a Turing machine does is read and write from a piece of tape.[3]
  • A much better way to write a Turing machine is with a diagram like above.[3]
  • We define the symbols a Turing machine works with.[3]
  • In other words, any algorithm ever can be built on a Turing machine.[3]
  • A Turing machine is a hypothetical machine thought up by Alan Turing.[4]
  • Conceptually, the Turing machine consists of an infinite tape and a tape head.[4]
  • We can simulate Turing machines (with finite tape) on our computers, but they are notoriously cumbersome to program.[4]
  • The machines discussed in this article are not the same as the hypothetical Turing machine as Alan Turing defined it.[4]
  • Section 2 provides some basic notations about Turing machine, Rubel’s EAC model, and the uEAC.[5]
  • A Turing machine can be seen as a state machine; at each moment the machine is in one of a finite number of states.[5]
  • Consider an example of single tape Turing machine with three states and is the initial state.[5]
  • In Figure 1, states of the Turing machine are represented by circles, with the concentric circle being the initial state .[5]
  • We will begin by constructing a Turing machine for the language L = {anbncn}.[6]
  • We will be adding a lot of states to create a Turing machine for L = {anbncn}.[6]
  • The value in the first box represents the current value under the head of the Turing machine.[6]
  • Add the transitions in your screen below to your Turing machine.[6]
  • It was late one night when I was starting my problem set on writing a turing machine to compute some operation.[7]
  • *position* position)) ;; The following are the procedures that implement the Turing machine.[7]
  • A turing machine consists of a tape of infinite length on which read and writes operation can be performed.[8]
  • Below, you can see the initial configuration of a Turing machine on the input 101001: .[9]
  • In 1936, Turing defined Turing machines as a universal model of computation on natural numbers.[9]
  • This means that all computable functions you can imagine can be computed by a Turing machine.[9]
  • He considered Turing machines with 2 symbols, and defined the functions S(n,2) and Sigma(n,2).[9]
  • A Turing machine consists of a line of cells known as the "tape", together with a single active cell, known as the "head".[10]
  • Any particular Turing machine is defined by a rule which specifies what the head should do at each step.[10]
  • Not every Turing machine has this property; many can only behave in very simple ways.[10]
  • A universal Turing machine has the property that it can emulate any other Turing machine---or indeed any computer or software system.[10]
  • Then run the instructions two more times and see if you can figure out what this Turing machine does.[11]
  • So this Turing machine is designed to flip bits.[11]
  • The instructions for this Turing machine only had one state, but more complex Turing machines can be built using multiple states.[11]
  • In this step, we’re going to have a look at Turing machines, which were hypothetical computers invented by Alan Turing in 1936.[11]
  • next → ← prev Turing Machine Turing machine was invented in 1936 by Alan Turing.[12]
  • There are various features of the Turing machine: It has an external memory which remembers arbitrary long sequence of input.[12]
  • Thus a common set of alphabets can be used for the Turing machine.[12]
  • The main advantage of the Turing machine is we have a tape head which can be moved forward or backward, and the input tape can be scanned.[12]
  • In its simplest form, a Turing machine is composed of a "tape", a ribbon of paper of indefinite length.[13]
  • The Turing machine is said to be in a certain "state".[13]
  • We then say a Turing machine is emulating another one (the one on the tape).[13]
  • the same computational capabilities than a Turing machine is to see if it can emulate a Turing machine.[13]
  • A Turing machine is an abstract computational device that can be in one of a finite set of possible states.[14]
  • The computational complexity of an algorithm is measured by the number of steps required by a Turing machine to run through the algorithm.[14]
  • A Turing machine as defined above is a deterministic machine.[14]
  • For each sequence of choices, the sequence of transitions corresponds to a sequence of steps executed by a deterministic Turing machine.[14]
  • To show there were algorithms that Turing machines would run indefinitely and inconclusively was a way of showing Hilbert was mistaken.[15]
  • , Turing noted that people are really Turing machines.[15]
  • A Turing machine is a very simple machine, but, logically speaking, has all the power of any digital computer.[16]
  • A Turing machine processes an infinite tape.[16]
  • At any time, the Turing machine has a read/write head positioned at some square on the tape.[16]
  • The very simplicity of a Turing machine makes it a challenge to program one to perform a specific computation.[16]
  • As shown in the animation above, a Turing machine consists of a tape that is initialized with a string of symbols.[17]
  • The table below describes a simple Turing machine that takes a string of 1 1 1’s as input and doubles it.[17]
  • A state register stores the state of the Turing machine.[18]
  • The heart of the turing machine is the read-write head.[19]
  • As Turing claimed, any process that can be naturally called an effective procedure is realized by a Turing machine.[20]
  • If the Turing machine halts for all inputs, then the function computed is defined for all arguments and we call it total computable.[20]
  • It is possible to give an effective (computable) one-to-one pairing between natural numbers and Turing machines.[20]
  • The last reference contains an excellent discussion of Turing machines, their computations, and related machines.[20]
  • Turing completeness is the ability for a system of instructions to simulate a Turing machine.[21]
  • The Turing machine mathematically models a machine that mechanically operates on a tape.[21]
  • A state register that stores the state of the Turing machine, one of finitely many.[21]
  • that stores the state of the Turing machine, one of finitely many.[21]
  • There are just six types of fundamental operation that a Turing machine performs in the course of a computation.[22]
  • It is a remarkable fact that none of these computers can outdo a Turing machine.[22]
  • Despite the Turing machine's austere simplicity, it is capable of computing anything that any computer on the market can compute.[22]
  • Indeed, since it is an abstract or notional machine, a Turing machine can compute more than any physical computer.[22]
  • They were first named ‘Turing machines’ by Alonzo Church in a review of Turing’s paper (Church 1937).[23]
  • Turing introduced Turing machines in the context of research into the foundations of mathematics.[23]
  • Another typical format to represent Turing machines and which was also used by Turing is the transition table.[23]
  • Thus, Post introduced a modified version of the Turing machine.[23]
  • A template for specifying a 3-state, 2-color Turing machine is shown above using a form of notation due to Wolfram (2002).[24]
  • An example 3-state, 2-color Turing machine is illustrated above (Wolfram 2002, p. 78).[24]
  • Determining whether a Turing machine will ever halt for a given input and set of rules is called the halting problem.[24]
  • For an -state binary Turing machine, the number of 1s written for a busy beaver is denoted .[24]
  • In section two, let's learn about LEDs, GPIO pins, resistors, and python, before embarking on building our Turing machine![25]

소스

  1. ↑ Probabilistic Turing machine
  2. ↑ 2.0 2.1 Neural Turing Machines: Perils and Promise
  3. ↑ 3.0 3.1 3.2 3.3 What’s a Turing Machine? (And Why Does It Matter?)
  4. ↑ 4.0 4.1 4.2 4.3 We are all Turing machines.
  5. ↑ 5.0 5.1 5.2 5.3 Simulation of Turing Machine with uEAC-Computable Functions
  6. ↑ 6.0 6.1 6.2 6.3 Turing Machine
  7. ↑ 7.0 7.1 Universal Turing Machine
  8. ↑ Turing Machine in TOC
  9. ↑ 9.0 9.1 9.2 9.3 Turing machines
  10. ↑ 10.0 10.1 10.2 10.3 Wolfram 2,3 Turing Machine Research Prize : What is a Turing Machine?
  11. ↑ 11.0 11.1 11.2 11.3 Turing machines
  12. ↑ 12.0 12.1 12.2 12.3 Automata Turing Machine
  13. ↑ 13.0 13.1 13.2 13.3 Turing machine
  14. ↑ 14.0 14.1 14.2 14.3 Turing Machines - an overview
  15. ↑ 15.0 15.1 How Alan Turing found machine thinking in the human mind
  16. ↑ 16.0 16.1 16.2 16.3 AMS :: Feature Column from the AMS
  17. ↑ 17.0 17.1 Brilliant Math & Science Wiki
  18. ↑ Turing Machine Introduction
  19. ↑ A Turing Machine Overview
  20. ↑ 20.0 20.1 20.2 20.3 Turing machine
  21. ↑ 21.0 21.1 21.2 21.3 Turing machine
  22. ↑ 22.0 22.1 22.2 22.3 AlanTuring.net What is a Turing machine?
  23. ↑ 23.0 23.1 23.2 23.3 Turing Machines (Stanford Encyclopedia of Philosophy)
  24. ↑ 24.0 24.1 24.2 24.3 Turing Machine -- from Wolfram MathWorld
  25. ↑ Department of Computer Science and Technology – Raspberry Pi: Introduction: What is a Turing machine?

메타데이터

위키데이터

Spacy 패턴 목록

  • [{'LOWER': 'turing'}, {'LEMMA': 'machine'}]
  • [{'LOWER': 'deterministic'}, {'LOWER': 'turing'}, {'LEMMA': 'machine'}]
원본 주소 "https://wiki.mathnt.net/index.php?title=튜링_기계&oldid=51952"