A typology for characterizing human action in multisector dynamics models

J Yoon, P Romero‐Lankao, YCE Yang… - Earth's …, 2022 - Wiley Online Library
The role of individual and collective human action is increasingly recognized as a prominent
and arguably paramount determinant in shaping the behavior, trajectory, and vulnerability of …

Hybridization of reinforcement learning and agent-based modeling to optimize construction planning and scheduling

NS Kedir, S Somi, AR Fayek, PHD Nguyen - Automation in Construction, 2022 - Elsevier
Decision-making in construction planning and scheduling is complex because of budget
and resource constraints, uncertainty, and the dynamic nature of construction environments …

Assessing adaptive irrigation impacts on water scarcity in nonstationary environments—a multi‐agent reinforcement learning approach

F Hung, YCE Yang - Water Resources Research, 2021 - Wiley Online Library
One major challenge in water resource management is to balance the uncertain and
nonstationary water demands and supplies caused by the changing anthropogenic and …

Designing with information feedbacks: Forecast informed reservoir sizing and operation

F Bertoni, M Giuliani, A Castelletti… - Water Resources …, 2021 - Wiley Online Library
The value of streamflow forecasts to inform water infrastructure operations has been
extensively studied. Yet, their value in informing infrastructure design is still unexplored. In …

梯级水库深度强化学习长期随机优化调度研究

李文武, 周佳妮, 裴本林, 张一凡 - 水力发电学报, 2023 - slfdxb.cn
梯级水库调度相较于单库调度状态空间呈指数级增大, 为解决基于表格的强化学习方法在解决
梯级水库长期随机优化调度问题时面临的维数灾问题, 提出采用深度强化学习中的深度Q …

How do the properties of training scenarios influence the robustness of reservoir operating policies to climate uncertainty?

JS Cohen, HB Zeff, JD Herman - Environmental Modelling & Software, 2021 - Elsevier
Reservoir control policies provide a flexible option to adapt to the uncertain hydrologic
impacts of climate change. This challenge requires robust policies capable of navigating …

Valuing combinations of flexible planning, design, and operations in water supply infrastructure

K Willebrand, M Zaniolo, J Skerker… - Water Resources …, 2024 - Wiley Online Library
Uncertainty arising from climate change poses a central challenge to the long‐term
performance of many engineered water systems. Water supply infrastructure projects can …

[HTML][HTML] Aggregation–decomposition-based multi-agent reinforcement learning for multi-reservoir operations optimization

M Hooshyar, SJ Mousavi, M Mahootchi… - Water, 2020 - mdpi.com
Stochastic dynamic programming (SDP) is a widely-used method for reservoir operations
optimization under uncertainty but suffers from the dual curses of dimensionality and …

Fill-and-Spill: Deep Reinforcement Learning Policy Gradient Methods for Reservoir Operation Decision and Control

SS Tabas, V Samadi - Journal of Water Resources Planning and …, 2024 - ascelibrary.org
Abstract Changes in demand, various hydrological inputs, and environmental stressors are
among the issues that reservoir managers and policymakers face on a regular basis. These …

[PDF][PDF] Hybrid Fuzzy System Dynamics–Fuzzy Agent-Based Modeling of Construction Labor Productivity

NS Kedir - 2022 - era.library.ualberta.ca
Construction labour productivity (CLP) is a key performance indicator for determining the
success of construction undertakings, and notably affects the profitability of construction …