Sequential Decision Strategy of the AML Cooperative Group Studies

1990 ◽  
pp. 290-294
Author(s):  
A. Heinecke ◽  
M. C. Sauerland ◽  
T. Büchner
Keyword(s):  
Cooperative Group ◽  
Decision Strategy ◽  
Sequential Decision

Monitoring Water Resources through a Bayesian Optimization-based Approach using Multiple Surface Vehicles: The Ypacarai Lake Case Study

2021 ◽  
Author(s):  
Federico Peralta Samaniego ◽  
Sergio Toral Marín ◽  
Daniel Gutierrez Reina
Keyword(s):  
Water Quality ◽  
Mean Squared Error ◽  
Bayesian Optimization ◽  
Water Quality Parameter ◽  
Optimization Approach ◽  
Decision Strategy ◽  
Sequential Decision ◽  
Partition System ◽  
Autonomous Surface Vehicle ◽  
Voronoi Partition

<div>Bayesian optimization is a popular sequential decision strategy that can be used for environmental monitoring. In this work, we propose an efficient multi-Autonomous Surface Vehicle system capable of monitoring the Ypacarai Lake (San Bernardino, Paraguay) (60 km<sup>2</sup>) using the Bayesian optimization approach with a Voronoi Partition system. The system manages to quickly approximate the real unknown distribution map of a water quality parameter using Gaussian Processes as surrogate models. Furthermore, to select new water quality measurement locations, an acquisition function adapted to vehicle energy constraints is used. Moreover, a Voronoi Partition system helps to distributing the workload with all the available vehicles, so that robustness and scalability is assured. For evaluation purposes, we use both the mean squared error and computational efficiency. The results showed that our method manages to efficiently monitor the Ypacarai Lake, and also provides confident approximate models of water quality parameters. It has been observed that, for every vehicle, the resulting surrogate model improves by 38%.</div>

A sequential-decision strategy for abating climate change

Nature ◽  
1992 ◽  
Vol 357 (6376) ◽  
pp. 315-318 ◽  
Author(s):  
James K. Hammitt ◽  
Robert J. Lempert ◽  
Michael E. Schlesinger
Keyword(s):  
Climate Change ◽  
Decision Strategy ◽  
Sequential Decision

Automation Reliability and Decision Strategy: A Sequential Decision Making Model for Automation Interaction

2018 ◽  
Vol 62 (1) ◽  
pp. 144-148 ◽  
Author(s):  
Aditya Acharya ◽  
Andrew Howes ◽  
Chris Baber ◽  
Tom Marshall
Keyword(s):  
Decision Making ◽  
Information Search ◽  
Sequential Decision Making ◽  
Decision Strategy ◽  
Sequential Decision ◽  
Decision Strategies ◽  
Information Reliability ◽  
Decision Making Model ◽  
Different Levels

The question of how people make use of automation to support their decision making is becoming increasingly important. As computers provide ever greater input to the collection, analysis and interpretation of data, so they are more likely to be partners in decision making. However, when automation makes recommendations that the human disagrees with or that might be based on erroneous analysis, then this could result in a change in decision strategy. It is not simply a matter of ignoring or rejecting the recommendation but rather a matter of deciding how best to make use of the automation’s output. By modeling information search and decision strategies under different levels of information reliability, we demonstrate that it makes sense to adapt decision strategy to the information context.

scholarly journals Monitoring Water Resources through a Bayesian Optimization-based Approach using Multiple Surface Vehicles: The Ypacarai Lake Case Study

2021 ◽  
Author(s):  
Federico Peralta Samaniego ◽  
Sergio Toral Marín ◽  
Daniel Gutierrez Reina
Keyword(s):  
Water Quality ◽  
Mean Squared Error ◽  
Bayesian Optimization ◽  
Water Quality Parameter ◽  
Optimization Approach ◽  
Decision Strategy ◽  
Sequential Decision ◽  
Partition System ◽  
Autonomous Surface Vehicle ◽  
Voronoi Partition

<div>Bayesian optimization is a popular sequential decision strategy that can be used for environmental monitoring. In this work, we propose an efficient multi-Autonomous Surface Vehicle system capable of monitoring the Ypacarai Lake (San Bernardino, Paraguay) (60 km<sup>2</sup>) using the Bayesian optimization approach with a Voronoi Partition system. The system manages to quickly approximate the real unknown distribution map of a water quality parameter using Gaussian Processes as surrogate models. Furthermore, to select new water quality measurement locations, an acquisition function adapted to vehicle energy constraints is used. Moreover, a Voronoi Partition system helps to distributing the workload with all the available vehicles, so that robustness and scalability is assured. For evaluation purposes, we use both the mean squared error and computational efficiency. The results showed that our method manages to efficiently monitor the Ypacarai Lake, and also provides confident approximate models of water quality parameters. It has been observed that, for every vehicle, the resulting surrogate model improves by 38%.</div>

Human and Optimal Valuation in a Sequential Decision-Making Task With Uncertainty

2007 ◽  
Author(s):  
Kyler M. Eastman ◽  
Brian J. Stankiewicz ◽  
Alex C. Huk
Keyword(s):  
Decision Making ◽  
Sequential Decision Making ◽  
Sequential Decision
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