1 / 24

Lecture 21 Reducibility

Lecture 21 Reducibility. Many-one reducibility. For two sets A c Σ * and B c Γ * , A ≤ m B if there exists a Turing-computable function f: Σ * → Γ * such that x ε A iff f(x) ε B. Complete in r. e.

gamanda
Download Presentation

Lecture 21 Reducibility

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. Lecture 21 Reducibility

  2. Many-one reducibility • For two sets A cΣ* and B cΓ*, A ≤m B if there exists a Turing-computable function f: Σ* → Γ* such that x ε A iff f(x) ε B

  3. Complete in r. e. • An r. e. set A is complete in r. e. if for every r. e. set B, B ≤m A .

  4. Halting problem Theorem. K = { <x, M> | M accepts x } is complete in r. e. . Proof. (1) K is a r. e. set. (2) For any r. e. set A, there exists a DTM MA such that A = L(MA). For every input x of MA, define f(x) = <x, MA>. Then x ε A iff f(x) ε K .

  5. Remark • If (1) A is a r. e. set, and (2) K ≤m A, then A is complete in r. e.

  6. Nonempty • Nonempty = {M | L(M) ≠ Φ } is complete in r. e. Proof. (1) Nonempty is a r. e. set. Construct a DTM M* as follows: For each M, we may try every input of M, one by one. If M accepts an input, then M is accepted by M*.

  7. (2)K ≤m Nonempty. SupposeM’is a DTM accepting every input. For each input <x, M> of K, we define f(<x, M>) is a code of the TM M* behave as follows: on an input y, M* carry out the following computation: Step 1. M* simulates M on input x. If M accepts x, then go to Step 2. Step 2. M* simulates M’ on input y

  8. Therefore, <x, M> ε K => M accepts x => M* accepts every input y => f(<x, M>) = M* ε Nonempty <x, M> not in K => M doesn’t halt on x => M* doesn’t halt on y => L(M*) = Φ => f(<x, M>) not in Nonempty

  9. r. e. –hard • A set B is r. e.-hard if for every r. e. set A, A ≤m B Remark • Every complete set is r. e.-hard. • However, not every r. e.-hard set is complete. • Every r. e.-hard set is not recursive.

  10. All = {M | M accepts all inputs} • All is r. e. hard. • All is not r. e. • All is not complete.

  11. Empty = {M | L(M) = Φ} • Empty is not r. e. • We don’t know if Empty is r. e.-hard.

  12. r. e. property • A subsetPof TM codes is called a r. e. property if M εPand L(M’) = L(M) implyM’ εP. e.g., Nonempty, Empty, All are r. e. properties. Question: Give an example which is a subsets of TM codes, but not a r. e. property.

  13. Nontrivial • A r. e. property is trivial if either it is empty or it contains all r. e. set.

  14. Rice Theorem 1 Every nontrivial r. e. property is not recursive.

  15. Proof • Let P be a nontrivial r. e. property. For contradiction. Suppose P is a recursive set. So is its complement. • Note that either P or its complement P does not contains the empty set. Without loss of generality, assume that P does not contains the empty set.

  16. Since P is nontrivial, P contains a nonempty r. e. set A. • Let Ma be a TM accepting A, i.e., A=L(Ma). • We want to prove K ≤m P. • For each input <x,M> of K, we define f(<x, M>) to be a code of TM M* which behaves as follows. For each input y of M*, M* does the following:

  17. Step 1. M* simulates M on input x of M. If M accepts x, then go to Step 2. Step 2. M* simulates Ma on y. If Ma accepts y, then M* accepts y. Therefore, if <x, M> ε K then L(M*) = L(Ma) = A εP, and if <x, M> not in K, then L(M*) = Φ not in P

  18. Since K is not recursive and K ≤mP, we obtain a contradiction. Recursive = {M | L(M) is recursive} is not recursive. RE = {M | L(M) is r. e.} is trivial.

  19. Question: • Is K an r. e. property? • Is every r. e. property complete? • Is it true that for any r. e. property, either it or its complement is complete?

  20. Rice Theorem 2 A r. e. property P is r. e. iff the following three conditions hold: • If A εP and A c B for some r. e. set B, then B εP. (2) If A is an infinite set in P, then A has a finite subset in P. (3) The set of finite languages in P is enumerable, in the sense that there is a TM that generates the (possibly) infinite string code1#code2# …, where codeiis a code for the ith finite languages inP.

  21. The code for the finite language {w1, w2, …, wn} is [w1,w2,…,wn]. • In other words, there exists an r. e. set B that is a subset of codes of finite languages in P such that for every finite language F in P, B contains at least one code of F.

  22. Examples • All is not r. e. because All does not satisfy condition (2). • The complement of ALL is not r. e. because it does not satisfy condition (1). • Empty is not r. e. because it does not satisfy (1) • Nonempty is r. e. because it satisfies (1), (2) and (3).

  23. Given TMs M and M’, is it true that L(M)=L(M’)? A = {<M,M’> | L(M) = L(M’)} is not recursive. Proof.Empty ≤m A. Let Mo be a fixed TM such that L(Mo) = Φ. Define f(M) =<M, Mo>. Then, M ε Empty iff <M, Mo> ε A.

More Related