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Introduction to Computability Theory. Lecture12: Reductions Prof. Amos Israeli. Introduction. The rest of the course deals with an important tool in Computability and Complexity theories, namely: Reductions . - PowerPoint PPT Presentation
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Introduction to Computability Theory
Lecture12: ReductionsProf. Amos Israeli
The rest of the course deals with an important tool in Computability and Complexity theories, namely: Reductions.
The reduction technique enables us to use the undecidability of to prove many other languages undecidable.
Introduction
2
TMA
A reduction always involves two computational problems. Generally speaking, the idea is to show that a solution for some problem A induces a solution for problem B. If we know that B does not have a solution, we may deduce that A is also insolvable. In this case we say that B is reducible to A.
Introduction
3
In the context of undecidability: If we want to prove that a certain language L is undecidable. We assume by way of contradiction that L is decidable, and show that a decider for L, can be used to devise a decider for . Since is undecidable, so is the language L.
Introduction
4
TMATMA
Using a decider for L to construct a decider for , is called reducing L to .
Note: Once we prove that a certain language L is undecidable, we can prove that some other language, say L’ , is undecidable, by reducing L’ to L.
Introduction
5
TMA TMA
1. We know that A is undecidable.
2. We want to prove B is undecidable.
3. We assume that B is decidable and use this assumption to prove that A is decidable.
4. We conclude that B is undecidable.
Note: The reduction is from A to B.
Schematic of a Reduction
6
1. We know that A is undecidable. The only undecidable language we know, so far, is whose undecidability was proven directly. (In the discussion you also proved directly that is undecidable). So we pick to play the role of A.
2. We want to prove B is undecidable.
Demonstration
7
TMHALT
TMA
TMA
2. We want to prove B is undecidable. We pick to play the role of B that is: We want to prove that is undecidable.
3. We assume that B is decidable and use this assumption to prove that A is decidable.
Demonstration
8
TMHALT
TMHALT
3. We assume that B is decidable and use this assumption to prove that A is decidable.In the following slides we assume (towards a contradiction) that is decidable and use this assumption to prove that is decidable.
4. We conclude that B is undecidable.
Demonstration
9
TMA
TMHALT
Consider
Theorem
is undecidable.
Proof
By reducing to .
The “Real” Halting Problem
10
wMwMHALTTM on haltsTM that a is ,
TMHALT
TMATMHALT
Assume by way of contradiction that is decidable.
Recall that a decidable set has a decider R: A TM that halts on every input and either accepts or rejects, but never loops!.
We will use the assumed decider of to devise a decider for .
Discussion
11
TMHALT
TMHALT
TMA
Recall the definition of :
Why is it impossible to decide ?
Because as long as M runs, we cannot determine whether it will eventually halt.
Well, now we can, using the decider R for .
Discussion
12
TMA
TMA
wMwMATM acceptsTM that a is ,
TMHALT
Assume by way of contradiction that is decidable and let R be a TM deciding it. In the next slide we present TM S that uses R as a subroutine and decides . Since is undecidable this constitutes a contradiction, so R does not exist.
Proof
13
TMHALT
TMA TMA
S=“On input where M is a TM:
1. Run R on input until it halts.
2. If R rejects, (i.e. M loops on w ) - reject.
(At this stage we know that R accepts, and we conclude that M halts on input w.)
3. Simulate M on w until it halts.
4. If M accepts - accept, otherwise - reject. “
Proof (cont.)
14
wM ,
wM ,
In the discussion, you saw how Diagonalization can be used to prove that is not decidable.
We can use this result to prove by reduction that is not decidable.
Another Example
15
TMA
TMHALT
Note: Since we already know that both and are undecidable, this new proof does not add any new information. We bring it here only for the the sake of demonstration.
Another Example
16
TMA
TMHALT
1. We know that A is undecidable. Now we pick to play the role of A.
2. We want to prove B is undecidable. We pick to play the role of B, that is: We want to prove that is undecidable.
3. We assume that B is decidable and use this assumption to prove that A is decidable.
Demonstration
17
TMHALT
TMA
TMA
3. We assume that B is decidable and use this assumption to prove that A is decidable.In the following slides we assume that is decidable and use this assumption to prove that is decidable.
4. We conclude that B is undecidable.
Demonstration
18
TMA
TMHALT
Let R be a decider for . Given an input for , R can be run with this input :If R accepts, it means that .This means that M accepts on input w. In particular, M stops on input w. Therefore, a decider for must accept too.wM ,
Discussion
19
wM ,
TMHALT
TMA
TMAwM ,
If however R rejects on input , a decider for cannot safely reject: M may be halting on w to reject it. So if M rejects w, a decider for must accept .
Discussion
20
TMHALT
wM ,
wM ,
TMHALT
How can we use our decider for ?The answer here is more difficult. The new decider should first modify the input TM, M, so the modified TM, , accepts, whenever TM M halts.
Since M is a part of the input, the modification must be a part of the computation.
Discussion
21
TMA
1M
Faithful to our principal “ If it ain’t broken don’t
fix it”, the modified TM keeps M as a subroutine, and the idea is quite simple:Let and be the accepting and rejecting states of TM M, respectively. In the modified TM, , and are kept as ordinary states.
Discussion
22
acceptq
1M
rejectq
acceptq rejectq
We continue the modification of M by adding a new accepting sate . Then we add two new transitions: A transition from to , and another transition from to .
This completes the description of . It is not hard to verify that accepts iff M halts.
acceptnq
Discussion
23
acceptq
rejectq
acceptnq
acceptnq
1M
1M
Discussion
24
acceptnq
1M
acceptq
rejectq
M
The final description of a decider S for is:
S=“On input where M is a TM:
1. Modify M as described to get .
2. Run R, the decider of with input .
3. If R accepts - accept, otherwise - reject. ”
Discussion
25
TMHALT
TMA
1M
wM ,1
wM ,
It should be noted that modifying TM M to get , is part of TM S, the new decider for , and can be carried out by it.
It is not hard to see that S decides . Since
is undecidable, we conclude that is undecidable too.
Discussion
26
1M
TMHALT
TMHALT
TMHALTTMA
We continue to demonstrate reductions by showing that the language , defined by
is undecidable.
Theorem
is undecidable.
The TM Emptiness Problem
27
M AndTM a is LMMETM
TME
TME
The proof is by reduction from :
1. We know that is undecidable.
2. We want to prove is undecidable.
3. We assume toward a contradiction that is decidable and devise a decider for .
4. We conclude that is undecidable.
Proof Outline
28
TME
TMA
TMA
TMATME
TME
Assume by way of contradiction that is decidable and let R be a TM deciding it. In the next slides we devise TM S that uses R as a subroutine and decides .
Proof
29
TME
TMA
Given an instance for , , we may try to run R on this instance. If R accepts, we know that . In particular, M does not accept w so a decider for must reject .
Proof
30
TMA
ML
wM ,
wM ,
TMA
What happens if R rejects? The only conclusion we can draw is that . What we need to know though is whether .
In order to use our decider R for , we once again modify the input machine M to obtain TM :
Proof
31
ML
MLw
TME
1M
We start with a TM satisfying .
Description of___
32
1M
MLML 1
1Macceptq
rejectq
M
startq
acceptnq
rejectnq
startnq
wM
wMwML
rejects if
accepts if 1
Now we add a filter to divert all inputs but w.
Description of___
33
1M
wx
wx
1Macceptq
rejectq
M
startq
acceptnq
rejectnq
startnq
wx filter
no
yes
TM has a filter that rejects all inputs excepts w, so the only input reaching M, is w.
Therefore, satisfies:
wM
wMwML
rejects if
accepts if 1
Proof
34
1M
1M
Here is a formal description of :
“On input x :
1. If - reject . 2. If - run M on w and accept if M accepts. ”
Note: M accepts w if and only if .
Proof
35
wx 1M
wx
1ML
1M
S=“On input where M is a TM:
1. Compute an encoding of TM . 2. Run R on input .
3. If R rejects - accept, otherwise - reject.
Proof
37
wM ,
1M 1M
1M
Recall that R is a decider for . If R rejects the modified machine , , hence by the specification of , , and a decider for must accept .If however R accepts, it means that , hence , and S must reject . QED
Proof
38
1M
TME
1ML
MLw1M
TMA
1ML
wM ,
MLw wM ,
We continue to demonstrate reductions by showing that the language :
is undecidable.
Theorem
is undecidable.
_______ is undecidable
39
TMREGULAR
TMREGULAR
TMREGULAR
RegularIS M AndTM a is LMMREGULARTM
The proof is by reduction from :
1. We know that is undecidable.
2. We want to prove is undecidable.
3. We assume that is decidable and devise a decider for .
4. We conclude that is undecidable.
Proof Outline
40
TMA
TMA
TMA
TMREGULAR
TMREGULAR
TMREGULAR
Consider an instance of ATM . Once again, the
idea is to transform TM M to another TM, , such that is regular if and only if .
Once we have such a machine we can run a decider for with as input, and accept , if the decider accepts.
Proof
41
TMAwM ,
wM ,
2M 2ML
TMREGULAR 2M
wM ,
Here the idea is to devise a TM that satisfy:
.
Description of___
42
2M
wMn
wMML
nn rejects if 0|10
accepts if *
2
TM M2 is obtained as follows:
1. Start with M.
2. Add a filter in front of M such that for every input x:
2.1 If x is of the form 0n1n - accept. 2.2 Send w to M – If M accepts - accept.
Description of___
43
2M
We start with a TM satisfying .
Description of___
44
2M
MLML 2
2M
M
rejectq
acceptq
startq
acceptnq
rejectnq
startnq
Add a filter to accept all inputs of form .
Description of___
45
1M
nnx 102M
M
rejectq
acceptq
startq
acceptnq
rejectnq
startnq
nn10filter
no
yes
w
nn10
“On input x :
1. If x has the form , accept . 2. If x does not have this form, run M on w and accept if M accepts w . ”
Note: If M accept w then . If M does not accepts w then .
Proof
46
nn10
2M
0|102 nML nn
*2 ML
Now consider S:
“On input :1. Construct as described using .
2. Run R on .
3. If R accepts (Meaning ) - accept , otherwise ( ) - reject .”
Proof
47
S wM ,
2M wM ,
2M
*2 ML
0|102 nML nn
Consider
Theorem
is undecidable.
TM Equivalence is Undecidable
48
2121, MLMLMMEQTM
TMEQ
The proof is by reduction from . We have to show that if is decidable, so is .The idea is very intuitive: In order to check that a language of TM M is empty, as required by , we will check whether M is equivalent to a TM that rejects all its inputs.
Proof
49
TME
ML
TMEQ TME
TME
S=“On input , where M is a TM:
1. Run R on input where is a TM that rejects all its inputs.
2. If R accepts – accept, otherwise – reject .
If R decides , S decides . Since is undecidable, so is . QED
Proof
50
M
1, MM 1M
TMEQ TME
TMEQ
TME
Mapping Reductions are the most common reductions in Computer Science. In this lecture we define mapping reductions and demonstrate the way in which they are used.
Mapping Reductions
51
The idea of a mapping reduction is very simple: If the instances (candidate elements) of one language, say A, are mapped to the instances of another language, say B, by a computable mapping M in a way that iff , then a decider for B can be used to devise a decider for A.
Mapping Reductions
52
AI BIM
Let A and B be two languages over . A function is a computable function if there exists a TM M such that for every , if M computes with input w it halts with on its tape.
Computable Functions
53
**: f
*
*w
wf
1. Let m and n be natural numbers, let be a string encoding both m and n, and let be the string representing their sum. The function ,, is computable.
2. The function is a computable function.
Can you devise TM-s to compute f and g?
Examples of Computable Functions
54
nmnmf ,
rwwg
nm,
nm
3. Let be an encoding of TM M and let be an encoding of another TM M’ satisfying:1. .2. TM M’ never makes two steps in the same
head direction.The function t defined below is computable:
Examples of Computable Functions
55
M
'MLML
TM any of ecodingnot is if
TM of ecoding an is if '
M
MMMMt
'M
Let A and B be two languages over . A computable function is a mapping reduction from A to B if for every it holds that follows: For each it holds that iff . The function f is called reduction of A to B. The arguments of the reduction are often called instances.
Mapping Reductions
56
**: f
*
AI
*I
BIf
If there exists a mapping reduction from A to B, We say that A is mapping reducible to B and denote it by .
If language A is mapping reducible to language B, then a solution for B, can be used to derive a solution for A. This fact is made formal in the following theorem:
Mapping Reductions
57
BA m
If and B is decidable, then A is decidable.
Theorem
58
BA m
Let M be a decider for B and let f be the reduction from A to B. Consider TM N:
N=“On input w :
1. Compute .
2. Run M on and output whatever M outputs. “
Clearly N accepts iff . QED
Proof
59
wf
wf
Bw
If and A is undecidable, then B is undecidable.
Corollary
60
BA m
The previous corollary is our main tool for proving undecidability.
Notice that in order to prove B undecidable we reduce from A which is known to be undecidable to B. The reduction direction is often a source of errors.
A similar tool is used in Complexity theory.
Discussion
61
At the beginning of this lecture we looked at
and proved that it is undecidable.
Now, we prove this theorem once more by demonstrating a mapping reduction from to .
The Halting Problem Revisited
62
wMwMHALTTM on haltsTM that a is ,
TMHALTTMA
The mapping reduction is presented by TM F :
F=“On input :
1. Construct TM M’ .
M’=“On input x:
1. Run M on x.
2. if M accepts accept.
3. If M rejects, enter a loop. “
2. Output . “
The Halting Problem Revisited
63
wM ,
wM ,'
What happens if the input does not contain a valid description of a TM?
By the specification of we know that in this case . Therefore in this case TM F should output any string s satisfying .
The Halting Problem Revisited
64
wM ,
TMA
TMAwM ,
TMHALTs