Polynomial-Time Reductions



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Polynomial-Time Reductions

For simplicity, we first consider distributional decision problems. Such a problem is comprised of a set of instances that are either positive or negative for the underlying decision problem, and a probability distribution on these instances. It is customary to specify only the set of positive instances, and we are concerned only with instances with positive probability. Under such a convention, we use to denote a distributional decision problem, where is the set of all positive instances with . The problem is to decide, for a given instance with , whether . If , then is called a distributional NP decision problem.

Denote by AP the class of all distributional decision problems such that is solvable in time polynomial on -average.

Let be a function with input distribution . It is reasonable to define the output distribution on , denoted by , to carry all the weights of those instances with . Namely, for all , . Denote by the distribution function of , so . Reductions from to should be closed for AP, meaning that if then so is . One way to guarantee this is to require that efficiently reduce to as in the worst case, and that it should not reduce ``frequent" instances of to ``rare" instances of . This means that the induced weight on the output should be bounded above (within a polynomial factor) by the weight on according to the distribution of . Namely, .gif If , it follows that there exists a distribution such that, for all , it holds that and ,gif which turns out to be sufficient for defining reductions. Levin [Lev86] defined reductions based on these ideas, and their current forms, namely Definitions 3.2 and 3.3, were given by Gurevich in [Gur91a].

 

 

 

If a reduction is one-one, then it is straightforward to see that iff . This observation is useful in proving completeness results. In the sequel, we will often use ``p-time" to denote ``polynomial-time," and ``ap-time" to denote ``average polynomial-time."

 

Proof.(1) Let be a p-time reduction from to . Then there are a distribution and a polynomial such that, for all , , and, for all , . Since , is deterministically decidable in time where, for some ,

For any , . Since is p-time computable, there is a such that for all but finitely many . Let . Then . It follows that is polynomial on -average, and so then also is

Thus, deciding ``?'' can be carried out in time plus the time to compute , and so . The proof of (2) is straightforward.


next up previous contents
Next: Polynomial-Time Computable Distributions Up: Average-Case Completeness Previous: Average-Case Completeness



Jie Wang
Tue Feb 4 13:48:58 EST 1997