【摘 要】
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In a distributed system, one of themost important things is to establish an assignment method fordistributing tasks. It is assumed that a distributed system doe
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In a distributed system, one of themost important things is to establish an assignment method fordistributing tasks. It is assumed that a distributed system does nothave a central administrator, all independent processing units in this systemwant to cooperate for the best results, but they cannot know theconditions of one another. So in order to undertake the tasks inadmirable proportions, they have to adjust their undertaking tasks onlyby self-learning. In this paper, the performance of thissystem is analyzed by Markov chains, and a robust method of self-learningfor independent processing units in this kind of systems is presented.This method can lead the tasks of the system to be distributed very wellamong all the independent processing units, and can also be used tosolve the general assignment problem.
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