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Open AccessArticle

Algorithm for Base Action Set Generation Focusing on Undiscovered Sensor Values

by Sho Yamauchi 1,* and Keiji Suzuki 2
1
Department of Computer Science, Kitami Institute of Technology, 165 Koencho, Kitami, Hokkaido 090-8507, Japan
2
Department of Complex and Intelligent Systems, Future university hakodate, 116-2, Kameda-Nakanocho, Hakodate 041-8655, Japan
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(1), 161; https://doi.org/10.3390/app9010161
Received: 26 November 2018 / Revised: 27 December 2018 / Accepted: 29 December 2018 / Published: 4 January 2019
(This article belongs to the Special Issue Advanced Mobile Robotics)
Previous machine learning algorithms use a given base action set designed by hand or enable locomotion for a complicated task through trial and error processes with a sophisticated reward function. These generated actions are designed for a specific task, which makes it difficult to apply them to other tasks. This paper proposes an algorithm to obtain a base action set that does not depend on specific tasks and that is usable universally. The proposed algorithm enables as much interoperability among multiple tasks and machine learning methods as possible. A base action set that effectively changes the external environment was chosen as a candidate. The algorithm obtains this base action set on the basis of the hypothesis that an action to effectively change the external environment can be found by observing events to find undiscovered sensor values. The process of obtaining a base action set was validated through a simulation experiment with a differential wheeled robot. View Full-Text
Keywords: action generation; robot motion; undiscovered sensor values; differential wheeled robot action generation; robot motion; undiscovered sensor values; differential wheeled robot
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Yamauchi, S.; Suzuki, K. Algorithm for Base Action Set Generation Focusing on Undiscovered Sensor Values. Appl. Sci. 2019, 9, 161.

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