Exceeding the Efficiency of Distributed Approximate Algorithms Enabling by the Multiplexing Method
Distributed constraint optimization problems have attracted attention as a method for resolving distribution problems in multiagent environments. In this paper, the authors propose a multiplex method aiming to improve the efficiency of a distributed nondeterministic approximate algorithm for distributed constraint optimization problems. Since much of the calculation time is used to transmit messages, improving efficiency using a multiplex calculation of distributed approximate algorithms might be feasible on the presupposition that the calculation time of each node or a small change in message length has no direct impact. The authors conducted a theoretical analysis of efforts to improve efficiency using a multiplex calculation of distributed approximate algorithms using extreme value theory and verifying with an experiment of a simple algorithm. A significant reduction in calculation time and improvement in the quality of the solution was ascertained, as a result of the experiment.
KeywordsMultiagent System Approximate Algorithm Message Length Multiplex Method Depth First Search Tree
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