Results 101 to 110 of about 154,147 (272)
Graph‐based imitation and reinforcement learning for efficient Benders decomposition
AIChE Journal, EarlyView.Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman +3 more
wiley +1 more source
How Sensitive Are Retirement Decisions to Financial Incentives: A Stated Preference Analysis [PDF]
We study effects of financial incentives on the retirement age using stated preference data. Dutch survey respondents were given hypothetical retirement scenarios describing age(s) of (partial and full) retirement and replacement rate(s).
van Soest, Arthur, Voňková, Hana
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The Challenge of Handling Structured Missingness in Integrated Data Sources
Advanced Intelligent Discovery, EarlyView.As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson +6 more
wiley +1 more source
Steering the Shape‐shifting of Bullvalene‐PdII Complexes Through Steric and Geometric Strain
Angewandte Chemie, EarlyView.This study explores the use of bis‐pyridyl substituted bullvalenes as dynamic shape‐shifting ligands within cis‐capped PdII complexes. The ring position of the pyridyl nitrogen is critical, leading to a range of Pd2L2 metallacycles and simple PdL complexes, each with distinctive bullvalene isomer preferences (represented in the figure by A‐D isomer ...
André P. Birvé +2 more
wiley +2 more sources
, 2017 Are human perception and decision biases grounded in a form of rationality? You return to your camp after hunting or gathering. You see the grass moving. You do not know the probability that a snake is in the grass.
De Lara, Michel
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Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Advanced Intelligent Discovery, EarlyView.Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
The cost-utility of school-based first permanent molar sealants programs: a Markov model
BMC Oral Health, 2019 Background Evidence of the cost-effectiveness of school-based first permanent molar sealants programs is not yet fully conclusive. The aim of this study was to determine the incremental cost-utility ratio (ICUR) of school-based prevention programs for ...
Gerardo Espinoza-Espinoza +4 more
doaj +1 more source
Optimal Coordination of Wind Power and Pumped Hydro Energy Storage
Energies, 2019 A study combining wind power with pumped hydro energy storage for the Jordanian utility grid is presented. Three solvers of the Matlab optimization toolbox are used to find the optimal solution for the cost of energy in a combined on-grid system. Genetic
Hussein M. K. Al-Masri +3 more
doaj +1 more source
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai +3 more
wiley +1 more source
Risk-Sensitive Reinforcement Learning: A Constrained Optimization Viewpoint
, 2018 The classic objective in a reinforcement learning (RL) problem is to find a policy that minimizes, in expectation, a long-run objective such as the infinite-horizon discounted or long-run average cost.
A., Prashanth L., Fu, Michael
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