Algorithmic version of the local lemma

نویسنده

  • Uri Feige
چکیده

Theorem 1 If there is an assignment 0 < xi < 1 satisfying for every i: Pr[Ai] ≤ xi ∏ j|Aj∈Γ(Ai) (1− xj) then the probability that no event Ai happens is at least ∏m i=1(1− xi) > 0. Observe that if the events were independent, the probability that no bad event happens would have been exactly ∏m i=1(1−Pr[Ai]). Hence in a sense, replacing the Pr[Ai] values by the larger xi values is the penalty paid in the conclusion of the local lemma for the variables not being truly independent. In many applications, the following uniform version of the local lemma suffices. Theorem 2 Let A be a collection of random events each happening with probability p. Assume that every event depends on at most d events (including itself). Namely, |Γ(Ai)|+ 1 ≤ d. Then if pde < 1 then with positive probability no event happens. Proof: The uniform version follows from the general version by picking xi = pe for every i. Then we have

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تاریخ انتشار 2010