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Any randomized algorithm may be interpreted as a randomized choice among deterministic algorithms, and thus as a mixed strategy for Alice. Similarly, a non-random algorithm may be thought of as a pure strategy for Alice. In any two-player zero-sum game, if one player chooses a mixed strategy, then the other player has an optimal pure strategy ...
A randomized algorithm is an algorithm that employs a degree of randomness as part of its logic or procedure. The algorithm typically uses uniformly random bits as an auxiliary input to guide its behavior, in the hope of achieving good performance in the "average case" over all possible choices of random determined by the random bits; thus either the running time, or the output (or both) are ...
Las Vegas algorithms were introduced by László Babai in 1979, in the context of the graph isomorphism problem, as a dual to Monte Carlo algorithms. [3] Babai [4] introduced the term "Las Vegas algorithm" alongside an example involving coin flips: the algorithm depends on a series of independent coin flips, and there is a small chance of failure (no result).
For every ε > 0, there is a PCP-verifier M for 3-SAT that reads a random string r of length ( ()) and computes query positions i r, j r, k r in the proof π and a bit b r. It accepts if and only if 'π ( i r ) ⊕ π ( j r ) ⊕ π ( k r ) = b r .
Grover's algorithm is optimal up to sub-constant factors. That is, any algorithm that accesses the database only by using the operator U ω must apply U ω at least a () fraction as many times as Grover's algorithm. [21] The extension of Grover's algorithm to k matching entries, π (N/k) 1/2 /4, is also optimal. [18]
[1] [2] The randomized mechanism is a direct-revelation mechanism - it starts by asking all agents to reveal their entire value-measures: Ask the agents to report their value measures. Use the existing algorithm/oracle to generate an exact division. Perform a random permutation on the consensus partition and give each partner one of the pieces.
Average-case analysis requires a notion of an "average" input to an algorithm, which leads to the problem of devising a probability distribution over inputs. Alternatively, a randomized algorithm can be used. The analysis of such algorithms leads to the related notion of an expected complexity. [2]: 28
Some problems which do not have a PTAS may admit a randomized algorithm with similar properties, a polynomial-time randomized approximation scheme or PRAS.A PRAS is an algorithm which takes an instance of an optimization or counting problem and a parameter ε > 0 and, in polynomial time, produces a solution that has a high probability of being within a factor ε of optimal.