PESA: Prioritized experience replay for parallel hybrid evolutionary and swarm algorithms - Application to nuclear fuel

We propose a new approach called PESA (Prioritized replay Evolutionary and Swarm Algorithms) combining prioritized replay of reinforcement learning with hybrid evolutionary algorithms. PESA hybridizes different evolutionary and swarm algorithms such as particle swarm optimization, evolution strategi...

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Bibliographic Details

Published in:	Nuclear engineering and technology Vol. 54; no. 10; pp. 3864 - 3877
Main Authors:	Radaideh, Majdi I., Shirvan, Koroush
Format:	Journal Article
Language:	English
Published:	Elsevier 01.10.2022 한국원자력학회
Subjects:	Hybrid evolutionary algorithms Nuclear fuel optimization Parallel optimization Priortized experience replay Reinforcement learning 원자력공학
ISSN:	1738-5733, 2234-358X
Online Access:	Get full text
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