Knowledge (XXG)

Adversary model

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If G is a c-competitive randomized algorithm against any adaptive online adversary, and there is a randomized d-competitive algorithm against any oblivious adversary, then G is a randomized (c * d)-competitive algorithm against any adaptive offline
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is sometimes called the strong adversary. This adversary knows everything, even the random number generator. This adversary is so strong that randomization does not help against it.
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If there is a randomized algorithm that is α-competitive against any adaptive offline adversary then there also exists an α-competitive deterministic algorithm.
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is sometimes referred to as the weak adversary. This adversary knows the algorithm's code, but does not get to know the randomized results of the algorithm.
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is sometimes called the medium adversary. This adversary must make its own decision before it is allowed to know the decision of the algorithm.
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The three common adversaries are the oblivious adversary, the adaptive online adversary, and the adaptive offline adversary.
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Index

Adversary (online algorithm)
computer science
online algorithm
competitiveness
A. Borodin
R. Karp
G. Tardos
A. Wigderson
Competitive analysis (online algorithm)
K-server problem
Online algorithm
Borodin, A.
Online Computation and Competitive Analysis
ISBN
978-0-521-56392-5
R. Karp
"On the Power of Randomization in On-line Algorithms"
doi
10.1007/BF01294260
Bibliography of papers on online algorithms
Categories
Analysis of algorithms
Online algorithms

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