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Acquisition of robot control rules by evolving MDDs

Masashi Sakai, Yutaro Tomoto, Masayoshi Kanoh, Tsuyoshi Nakamura, Hidenori Itoh

发表年份
2010
引用次数
2

摘要

A method in which multi-valued decision diagrams (MDDs) are used to acquire robot action rules is proposed. Kanoh et al. have proposed a method, which uses multi-terminal binary decision diagrams (MTBDDs), to acquire robot action rules. But the variables of MTBDDs can only take values of 0 or 1; multiple variables are needed to represent a single joint angle. This increases the number of variables and the MTBDDs that represent the action rules become complex. Here, a method that uses MDDs, in which a single variable can take on multiple values, is proposed and experimental results are shown comparing MTBDDs and MDDs through simulations to acquire robot action rules.

关键词

RobotComputer scienceAction (physics)Variable (mathematics)Artificial intelligenceMachine learningMathematics

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