Task Allocation Strategy Based on Game Theory in Group Computing
LIU Ming
PENG Cheng
MAN Junfeng
LIU Meibo
DU Kun
Abstract：The rapid development of big data promotes the progress of economy and technology,but the features,low value density,bring challenges to the big data.These features make that it need urgently complex cognitive reasoning,which is effectively solved by human-machine collaboration based crowd computing.However,crowd computing’s task allocation strategy is not maturity completely.some scholars have come up with a theme-aware task assignment framework,which solves task allocation to different professional background and knowledge level,but it does not deal with task allocation invol-ving same knowledge level and professional background,which makes higher computational efficiency.To deal with this problem,it propose a task allocation algorithm based on game theory,which detects the accuracy with same professional and knowledge level.The task allocation algorithm based on game theory,compared with randomly task allocation,shows the accuracy of game theory algorithm.
Keywords：crowd computinggame theorybig datatask allocation
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 2144-2147,2173 )