A Novel Approach Based on Reinforcement Learning for Finding Global Optimum

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ISSN Print: 2325-7105
ISSN Online: 2325-7091
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"A Novel Approach Based on Reinforcement Learning for Finding Global Optimum"
written by Cenk Ozan, Ozgur Baskan, Soner Haldenbilen,
published by Open Journal of Optimization, Vol.6 No.2, 2017

has been cited by the following article(s):

[1]	Design method for a wideband non-uniformly spaced linear array using the modified reinforcement learning algorithm
	Sensors, 2022

[2]	Design Approach of a Wideband Non-Uniformly Spaced Linear Array Based on Reinforcement Learning to Suppress Multiple Interference Signals
	The Journal of Korean Institute …, 2022

[3]	다중 간섭 신호 억제를 위한 강화학습 기반의 광대역 Non-Uniformly Spaced Linear Array 설계 기법
	한국전자파학회논문지, 2022

[4]	강화학습을 이용한 Non-Uniformly Spaced Planar Array 빔형성 설계 연구
	한국통신학회 …, 2022

[5]	Effective Routing in Vehicular Adhoc Network (VANET) using an Bio-inspired Algorithm: Enhanced Deep Reinforcement Learning (EDRL) for Secure Wireless …
	2021

[1]	An evolutionary variant of Q-learning applied to derivative-free optimization AIAA AVIATION 2023 Forum, 2023 DOI:10.2514/6.2023-4262

[2]	Design Method for a Wideband Non-Uniformly Spaced Linear Array Using the Modified Reinforcement Learning Algorithm Sensors, 2022 DOI:10.3390/s22145456

[3]	Design Approach of a Wideband Non-Uniformly Spaced Linear Array Based on Reinforcement Learning to Suppress Multiple Interference Signals The Journal of Korean Institute of Electromagnetic Engineering and Science, 2022 DOI:10.5515/KJKIEES.2022.33.10.811

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