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Bio-insect and artificial robot interaction using cooperative reinforcement learning

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Abstract
In this paper, we propose fuzzy logic-based cooperative reinforcement learning for sharing knowledge among autonomous robots. The ultimate goal of this paper is to entice bio-insects towards desired goal areas using artificial robots without any human aid. To achieve this goal, we found an interaction mechanism using a specific odor source and performed simulations and experiments [1]. For efficient learning without human aid, we employ cooperative reinforcement learning in multi-agent domain. Additionally, we design a fuzzy logic-based expertise measurement system to enhance the learning ability. This structure enables the artificial robots to share knowledge while evaluating and measuring the performance of each robot. Through numerous experiments, the performance of the proposed learning algorithms is evaluated. (C) 2014 Elsevier B.V. All rights reserved.
Author(s)
Son, Ji-HwanChoi, Young-CheolAhn, Hyo-Sung
Issued Date
2014-12
Type
Article
DOI
10.1016/j.asoc.2014.09.002
URI
https://scholar.gist.ac.kr/handle/local/14946
Publisher
ELSEVIER SCIENCE BV
Citation
Applied Soft Computing Journal, v.25, pp.322 - 335
ISSN
1568-4946
Appears in Collections:
Department of Mechanical and Robotics Engineering > 1. Journal Articles
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