An FRTDS Real-Time Simulation Optimized Task Scheduling Algorithm Based on Reinforcement Learning

An FRTDS Real-Time Simulation Optimized Task Scheduling Algorithm Based on Reinforcement Learning

This paper presents a deep reinforcement learning (DRL)-based task scheduling algorithm that is applied to an FPGA-based real-time digital simulation (FRTDS) system to generate arrangements to minimize the makespan of a task sequence with limited resources. The algorithm has two parts, which are syn...

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Bibliographic Details
Main Authors: Y. Guan, Bd. Zhang, Z. Jin
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
DQN
FPGA
power simulation
real-time
reinforcement learning
RTDS
Online Access:https://ieeexplore.ieee.org/document/9099208/

Internet

https://ieeexplore.ieee.org/document/9099208/

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