1 / 38

Turing Machines

Turing Machines. Chapter 3.1. Plan. Turing Machines(TMs) Alan Turing Church-Turing Thesis Definitions Computation Configuration Recognizable vs. Decidable Examples Simulator. Alan Turing. Alan Turing was one of the founding fathers of CS.

nicholas-zoie
Télécharger la présentation

Turing Machines

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Turing Machines Chapter 3.1

  2. Plan • Turing Machines(TMs) • Alan Turing • Church-Turing Thesis • Definitions • Computation • Configuration • Recognizable vs. Decidable • Examples • Simulator

  3. Alan Turing Alan Turing was one of the founding fathers of CS. • His computer model the Turing Machine(1936)was the inspiration for the electronic computer that came two decades later • Was instrumental in cracking the Nazi Enigma cryptosystem in WWII • Invented the “Turing Test” used in AI • The Turing Award. Pre-eminent award in Theoretical CS (called the “Nobel Prize” of CS)

  4. Church-Turing Thesis • Thesis- Every effectively calculable function is a computable function • Everything that is computable is computable by a Turing machine • The thesis remains a hypothesis • Despite the fact that it cannot be formally proven the Church–Turing thesis now has near-universal acceptance.

  5. Turing Machine • Most powerful machine so far… • Similar to a finite automata • Uses infinite tape as memory • Can both read from and write to the tape • Read/write head can move left/right • Accept/reject take affect immediately • Cannot solve all problems

  6. Comparison with Previous Models

  7. Formal Definition of a TM

  8. SuccessorProgram • Sample Rules: • If read 1, write 0, go right, repeat. • If read 0, write 1, HALT! • If read “”, write 1, HALT! • Using these rules on a tape containing the reverse binary representation of 47 we obtain:

  9. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  10. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  11. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  12. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  13. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  14. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  15. SuccessorProgram So the successor’s output on 111101 was 000011 which is the reverse binary representation of 48. Similarly, the successor of 127 should be 128:

  16. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  17. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  18. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  19. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  20. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  21. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  22. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  23. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  24. SuccessorProgram If read 1, write 0, go right, repeat. If read 0, write 1, HALT! If read “”, write 1, HALT!

  25. Drawing the machine • Draw the machine • Description • If read 1, write 0, go right, repeat. • If read 0, write 1, HALT! • If read “”, write 1, HALT!

  26. TM Dynamic Picture • A string w is accepted by M if after being put on the tape then letting M run, M eventually enters the accept state. Therefore, w is an element of L(M) - the language accepted by M. • We can formalize this notion as follows:

  27. TM Formal DefinitionDynamic Picture Suppose TM’s configuration at time t is given by uapxvwhere pis the current state, ua is what’s to the left of the head, x is what’s being read, and vis what’s to the right of the head. If d(p,x) = (q,y,R) then write: uapxv uayqv With resulting configuration uaypv at time t+1. If, d(p,x) = (q,y,L) instead, then write: uapxv uqayv There are also two special cases: • head is forging new ground –pad with the blank symbol  • head is stuck at left end –by def. head stays put NOTE: “” is read as “yields”

  28. TM outcomes Three possibilities occur on a given input w : • The TM M eventually enters qacc and therefore halts and accepts. (w  L(M) ) • The TM M eventually enters qrej orcrashes somewhere. M rejectsw . (w L(M) ) • Neither occurs! I.e., M never halts its computation and is caught up in an infinite loop, never reaching qacc or qrej.  In this case w is neither accepted nor rejected. However, any string not explicitly accepted is considered to be outside the accepted language. (w  L(M) )

  29. Recognizable vs. Decidable • Recognizable- The TM recognizes the language but doesn’t necessarily reach an accept or reject state (could loop FOREVER ) • Decidable- is recognizable and guaranteed to reach an accept or reject state (without the possibility for an infinite loop )

  30. Bit-shifting example

  31. 3.7 Diagram

  32. Fall 2010 Exam 2 Question 1 1) (25 pts) Give the full, formal description of a Turing Machine that accepts the following language: L = { w#wR | where w consists of only 0s and 1s and has length at least 1. } The input alphabet will be {0, 1, #}. The tape alphabet will include 0, 1, #, B, and any other symbols you choose to include in it. Give a simple intuitive description of what each state in the machine represents. And draw the diagram for this machine.

  33. Simulator • Accepts 4 or 5 tuples • (Start,input,NewState,output,Direction) • (Start,input,NewState,Direction OR output) • One tape • http://ironphoenix.org/tril/tm/

  34. END

More Related