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Decision Making Under Multi Task Based on Priority for Each Task

Takuya Masaki, Kentarou Kurashige

发表年份
2016
引用次数
5

摘要

In recent years, autonomous robots become to be desired to treat multi-task. A robot must decide a concrete action for plural objectives. Major researches try to realize this by weighted rewards. Weighted rewards can represent a human's intention easily. But weight of each task must change dynamically by a change of surrounding situation or of a robot status. Authors consider an independent learning for each task and selection of one concrete action from candidates of each learning. Authors propose a priority function to calculate priority for each task corresponding to surrounding situation or a robot status and propose a system which do decision making by using the priority function. Authors confirmed the usefulness of proposed method with simulation.

关键词

Task (project management)PluralComputer scienceAction (physics)RobotAction selectionFunction (biology)Artificial intelligenceSelection (genetic algorithm)Machine learning

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