Multiagent Reinforcement Learning for Project-Level Intervention Planning under Multiple Uncertainties-Reference-Cited by-同舟云学术

Multiagent Reinforcement Learning for Project-Level Intervention Planning under Multiple Uncertainties

Published:2023-03 Issue:2 Volume:39 Page:
ISSN:0742-597X
Container-title:Journal of Management in Engineering
language:en
Short-container-title:J. Manage. Eng.

Author:

Asghari Vahid¹,Biglari Ava Jahan²^ORCID,Hsu Shu-Chien³^ORCID

Affiliation:

1. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Hong Kong Polytechnic Univ., 181 Chatham Rd. South, Kowloon, Hong Kong.

2. School of Civil and Environmental Engineering, Univ. of Tehran, 16 Azar Ave., P.O. Box 11155-4563, Tehran, Iran. ORCID: .

3. Associate Professor, Dept. of Civil and Environmental Engineering, Hong Kong Polytechnic Univ., 181 Chatham Rd. South, Kowloon, Hong Kong (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management Science and Operations Research,Strategy and Management,General Engineering,Industrial relations,Building and Construction

Link

https://ascelibrary.org/doi/pdf/10.1061/JMENEA.MEENG-4883

Reference86 articles.

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2. Defining road service to facilitate road infrastructure asset management

3. Decision making methods to prioritise asset-management plans for municipal infrastructure

4. Managing engineering systems with large state and action spaces through deep reinforcement learning

5. ASCE. 2021. ASCE’s 2021 infrastructure report card. Reston, VA: ASCE.

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