Quantum-based approach for laboratory risk assessment and decision-making
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Improving risk assessment and conducting thorough cost-benefit analyses of the different proposed management options are of paramount importance to making informed decisions. However, getting a comprehensive picture of a complex, ambiguous and uncertain ri ...
This paper studies the operation of multi-agent networks engaged in multi-task decision problems under the paradigm of simultaneous learning and adaptation. Two scenarios are considered:one in which a decision must be taken among multiple states of nature ...
Research in nanoscience continues to bring forward a steady stream of new nanomaterials and processes that are being developed and marketed. While scientific committees and expert groups deal with the harmonization of terminology and legal challenges, risk ...
The visual inspection of existing infrastructure is a critical step for asset management, as the detection and quantification of damage must be useful to prioritise maintenance. In Switzerland, main inspections are made every five years for all road bridge ...
Making decisions is part and parcel of being human. Among a set of actions, we want to choose the one that has the highest reward. But the uncertainty of the outcome prevents us from always making the right decision. Making decisions under uncertainty can ...
Neighborhood-scale projects often commence with the conceptualization of several massing-schemes as potential design solutions. There is growing interest in using building performance simulation (BPS) to evaluate and rank such conceptual stage schemes in o ...
Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...
Recent natural disasters that seriously affected critical infrastructure (CI) with significant socio-economic losses and impact revealed the need for the development of reliable methodologies for vulnerability and risk assessment. In this paper, a risk-bas ...
Stochastic programming and distributionally robust optimization seek deterministic decisions that optimize a risk measure, possibly in view of the most adverse distribution in an ambiguity set. We investigate under which circumstances such deterministic de ...
In this work, we present a motion planning framework for automated vehicles to drive safely through intersections despite occlusions and the uncertain behavior of the surrounding vehicles. A context representation based on probably-free gaps is proposed as ...