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# Class 36: Halting Problem

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Halting Problem …

Halting Problem
Proving Non-Computability
Universal Turing Machines

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• 1. cs1120 Fall 2011David Evans16 November 2011 Halting Problems Hockey Team
• 2. RemindersPS7 Due (electronic) 11:59pm tonightExam 2 review sessions (Rice 442): Today, 7:30pm My Thursday office hours moved to 4-5pm Thursday, 6:30pmFriday’s class: Rice Hall Dedication 11am Dedication; noon-3pm Tours; 3pm Dean Kamen talk; 5pm Scavenger Hunt Office hours from now on are in “Davis Commons”! 2
• 3. PS8, Part 1Option C/W: Option J: Clear description of what you plan to do PS8 Part 1 posted on including: course site.1. Goal2. Target audience3. Plan Due next week Tuesday,4. Team, how you will 22 November (11:59pm) manage and distribute work 3
• 4. Impossibility Results Mathematics (Declarative Knowledge)Friday/Monday Gödel: Any powerful axiomatic system cannot be both complete and consistent If it is possible to express “This statement has no proof.” in the system, it must be incomplete or inconsistent. Computer Science (Imperative Knowledge) Are there (well-defined) problems that cannot beNow solved by any algorithm? Alan Turing (and Alonzo Church): Yes!
• 5. Impossibility of HaltsRecall how Gödel showed incompleteness of PM: Find a statement that leads to a contradiction Gödel’s statement: “This statement has no proof.” The HALTING Problem: Input: a string representing a Python program. Output: If evaluating the input program would ever finish, output true. Otherwise, output false. Assume halts(s) is a Python procedure that solves the HALTING problem. Is there an input that leads to a contradiction?
• 6. Hmm..let’s try self-reference! 6
• 8. Proving Non-Existence by Contradiction1. Show X is nonsensical.2. Show that if you have A you can make X.3. Therefore, A must not exist.
• 9. Proving Non-Existence by Contradiction1. Show X is nonsensical.2. Show that if you have A you can make X.3. Therefore, A must not exist. Noncomputability Incompleteness (Alan Turing) (Kurt Gödel)X = paradox procedure X = “This statement has noA = algorithm that solves proof.” HALTING Problem A = a complete and consistent axiomatic system
• 10. Halting Problem is Non-Computable 1. paradox leads to a contradiction. def paradox(): 2. If we have halts, an if halts(paradox()): algorithm that solves the while True: Halting Problem, we can define paradox. pass 3. Therefore, halts must not exist. Are there any other noncomputable problems?
• 11. Evaluates-to-3 ProblemInput: A string, s, representing a Python program.Output: True if s evaluates to 3; otherwise, False. Is “Evaluates-to-3” computable?
• 12. Proof by Contradiction1. Show X is nonsensical.2. Show that if you have A you can make X.3. Therefore, A must not exist. X = halts algorithm A = Evaluates-to-3 algorithm
• 13. Undecidability ProofSuppose we could define evaluates_to_3(s).that decides it. Could we define halts(s)?
• 14. Undecidability Proof def halts(s): return evaluates_to_3( cleanreturns(s) + return 3 Where cleanreturns(s) is a ) procedure that replaces all return x statements in s with x; return 3The only way the program s passed to evaluates_to_3 could not evaluateto 3, is if s doesn’t halt. (Note: assumes evaluating s cannot produce anerror, but we can use error handling to deal with this case.)
• 15. How convincing is our Halting Problem proof? 1. paradox leads to adef paradox(): contradiction. if halts(paradox()): 2. If we have halts, an algorithm that solves the Halting while True: Problem, we can define pass paradox. 3. Therefore, halts must not exist.“Proof” assumes Python exists and means exactly what it should!Python is too complex to believe this (and Turing didn’t have it, ofcourse!): need a simple and precise model of computation.
• 16. Turing’s Model: Turing Machine... # 1 0 1 1 0 1 1 1 0 1 1 0 1 1 1 # ... Infinite Tape: Finite set of symbols, one in each square Can read/write one square each step Start Input: # Controller: Input: 1 Limited (finite) Write: # Write: 0 number of states Move: Move: 1 Follow rules based 2 Input: 0 on current state and read symbol Write: # Input: 1 Input: 0 Move: Halt Write one square Write: 1 Write: 0 each step, move Move: Move: 3 left or right or halt, change state 16
• 17. Turing Machine SummaryModel Input, Output, and Scratch Memory Infinite tape, divided into discrete squares Each square can contain a single symbol from a finite alphabetModel Processing Finite State Machine Keep track of a finite state (in your head) Follow transition rules: next state = f(current state, input symbol) 17
• 18. Halting Problem for TMInput: a string describing a Turing Machine, MOutput: if M would eventually Halt, output True; otherwise, output False.Is there a Turing Machine that solves the Halting Problem for TMs? 18
• 19. Turing Machine State Infinite Tapez z z z z z z z z z z z z z z z z z z z TuringMachine ::= < Alphabet, Tape, FSM > ), X, L ), #, R Alphabet ::= { Symbol* } (, #, L 1 2: look for ( Tape ::= < LeftSide, Current, RightSide > Start (, X, R OneSquare ::= Symbol | # Current ::= OneSquare #, 1, - HALT #, 0, - LeftSide ::= [ Square* ] Finite State Machine RightSide ::= [ Square* ] Everything to left of LeftSide is #. Everything to right of RightSide is #. Although we typically draw TMs as pictures, we could write them down as strings in this language (which could be converted to whole numbers)
• 20. Enumerating Turing MachinesNow that we’ve decided how to describe Turing Machines, we can number themTM-5023582376 = balancing parensTM-57239683314 = less than function (Exam 1)TM- = Universal TM 3523796834721038296738259873TM- 3672349872381692309875823987609823712347823 = Angry Birds Not the real numbers – they would be much much much much much bigger!
• 21. Halting ProblemPythonic Halting Problem TM Halting ProblemInput: a string describing a Input: a string describing a Python program, P Turing Machine, MOutput: if evaluating P would Output: if M would eventually eventually finish, output Halt, output True; True; otherwise, output otherwise, output False. False.
• 22. Halting Problem “Proof”Pythonic Halting Problem TM Halting Problem HALTS(M) = TM that solves TM Halting def paradox(): Problem: input tape describes TM if halts(paradox()): M, output tape: #1 if M while True: halts, otherwise #0 pass PARADOX = TM that: 1. simulates HALTS(PARADOX) 2. Then, if tape is #1, loop forever; if tape is #0, HALT simulates? This proof assumes we can design a TM that simulates any other TM!
• 23. An Any TM Simulator Input: < Description of some TM M, w > Output: result of running M on wM Output Universal Tape Turing for running TM-Mw Machine starting on tape w
• 24. Manchester Illuminated Universal Turing Machine, #9from http://www.verostko.com/manchester/manchester.html
• 25. Universal Computing Machine 2-state, 3-symbol Turing machine proved universal by Alex Smith in 2007 Alex Smith, University of Birmingham
• 26. What This MeansIf you can: Keep track of a finite state Follow transition rules Read and write to memory you can simulate a universal Turing machine.A Turing machine can simulate the world’s most powerful supercomputer (it’ll just take a lot longer and will run out of memory)It is impossible to solve the Halting Problem for any computing system that can simulate a TM
• 27. Alan Turing (1912-1954)Published On Computable Numbers … (1936) Introduced the Halting Problem 5 years after Formal model of computation Gödel’s proof! (now known as “Turing Machine”)Codebreaker at Bletchley Park Led efforts to break Enigma Cipher Contributed to ColossusAfter the war: convicted of “gross indecency” (homosexuality, then a crime in Britain), forced to undergo hormone treatments, committed suicide eating cyanide apple
• 28. Prime Minister’s ApologyIt is no exaggeration to say that, without his outstandingcontribution, the history of World War Two could well havebeen very different. He truly was one of those individuals wecan point to whose unique contribution helped to turn thetide of war. The debt of gratitude he is owed makes it all themore horrifying, therefore, that he was treated soinhumanely....So on behalf of the British government, and all those wholive freely thanks to Alan’s work I am very proud to say:we’re sorry, you deserved so much better. Gordon Brown, 10 September 2009
• 29. ChargeBefore midnight tonight: submit PS7Exam Review Sessions: Today, 7:30pm; Thursday, 6:30pmFriday’s Class: Rice Hall DedicationMonday: Exam 2 outTuesday: PS8 Part 1 Due 29