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Peer-Review Record

Attention-Shared Multi-Agent Actor–Critic-Based Deep Reinforcement Learning Approach for Mobile Charging Dynamic Scheduling in Wireless Rechargeable Sensor Networks

Entropy 2022, 24(7), 965; https://doi.org/10.3390/e24070965
by Chengpeng Jiang 1,2, Ziyang Wang 3, Shuai Chen 1,2, Jinglin Li 1,2, Haoran Wang 1,2, Jinwei Xiang 1,2 and Wendong Xiao 1,2,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3:
Entropy 2022, 24(7), 965; https://doi.org/10.3390/e24070965
Submission received: 9 June 2022 / Revised: 9 July 2022 / Accepted: 9 July 2022 / Published: 12 July 2022
(This article belongs to the Topic Machine and Deep Learning)

Round 1

Reviewer 1 Report

The paper can be considered as a starting point for a future reseacth, but its actual contribution is poorly significant.  

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

This manuscript presents a new AMADRL-JSSRC algorithm to prolong the lifetime of wireless rechargeable sensor networks with a larger scale and reduce the number of death sensors based on th online control strategy. Overall, the manuscript is well prepared and the results are compared with baseline algorithms. Here are some minor suggestions:

 (1)In introduction, authors listed and compared a dozen algorithms including offline and online strategy. The performances, drawbacks and improvements of each algorithms vs proposed algorithm should be summarized and highlighted clearly by a table.

 (2)Section 4 is missing, it is suggested to move sections 5.1 and 5.2 to section 4 as experimental setup and results and move sections 5.3 and 5.4 to section 5 as discussion.

 

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

This paper is well written with clear background research and problem formulation. Few minor comments:

1. The definitions could be highlighted or written in other formats.

2. The paper has used a lot of abbreviations, the reviewer suggests having a list of abbreviations.

3. Should "Dis" be defined within section 2.1?

Author Response

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Author Response File: Author Response.docx

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