Reinforcement Learning and Automatic Control for Resilience of Maritime Container Ports-Reference-Cited by-同舟云学术

Reinforcement Learning and Automatic Control for Resilience of Maritime Container Ports

Published:2023-07-03 Issue: Volume: Page:
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Container-title:2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)
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Author:

Loose Davis C.¹,Eddy Timothy L.¹,Polmateer Thomas L.²,Hendrickson Daniel C.³,Moghadasi Negin¹,Lambert James H.¹

Affiliation:

1. University of Virginia,Dept. of Engineering Systems and Environment,Charlottesville,VA,USA

2. CCALS University of Virginia,Dept. of Engineering Systems and Environment,Charlottesville,VA,USA

3. Vice President of Strategy, Planning and Analytics Port of Virginia,Norfolk,VA,USA

Publisher

IEEE

Link

Reference35 articles.

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2. Applying expert knowledge to containership stowage planning: An empirical study;chou;Maritime Economics & Logistics,2018

3. MuZero general: open reimplementation of MuZero;duvaud;Github Repository,2020

4. Operations functional specifications: Norfolk international terminals optimization project;Port of Virginia (PoV),2018

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