14 papers · ranked by Valyu relevance
Thomas Bartz–Beielstein, Eva Bartz, Alexander Hinterleitner, Christoph Leitenmeier + 1 more
Existing experimental designs in industry are often unplanned, biased, and lack optimal space-filling properties, making them unrepresentative of the input space. This article presents an approach to improve such designs by increasing coverage quality while simultaneously optimizing experimental results. We utilize the…
María Luisa González-Rodríguez, Sonia Valverde-Cabeza, Enrique Pérez-Terrón, Antonio María Rabasco + 2 more
Background/Objectives: Clonazepam (CLZ), a BCS Class II drug, presents significant oral delivery challenges due to its low aqueous solubility. This study explores the systematic development of solid self-emulsifying drug delivery systems (S-SEDDS) using Quality by Design (QbD). The primary objective was to evaluate and…
Jan A. Calalo, Seth R. Sullivan, Nicholas R. Muscara, John Buggeln + 5 more
Humans spend a lifetime making decisions based on incoming sensory information and goals. Prominent theories of perceptual decision-making have described the components of deliber-ation process, yet they lack a unifying principle that governs how the nervous system tunes the deliberation process across multiple…
Olaf Frommann
Scalar objective functions are required when a multi-criteria optimization problem must yield a single preferred design rather than only a Pareto set. The choice of scalarization influences which compromise is selected, how preference parameters are interpreted, and whether non-supported Pareto regions can be reached.…
A. R. M., Wolfert
Preference aggregation is a core operation in multi-objective design optimisation and group decision-making, as it determines the best-fit-for-common-purpose alternative within complex socio-technical contexts. Since preferences are intrinsically linked to choice, they are subjective, inherently contextual, and reflect…
Kathelijne Coussement, Gert de Cooman, K. Vos
We discuss conditionalisation for Accept-Desirability models in an abstract decision-making framework, where uncertain rewards live in a general linear space, and events are special projection operators on that linear space. This abstract setting allows us to unify classical and quantum probabilities, and extend them…
Authors not listed
Realizing the promise of artificial intelligence (AI) to accelerate scientific progress and deliver technological impact depends on how effectively AI can be integrated into real-world decision- making processes. As Peter Norvig states, “Somewhat remarkably, almost all AI research until very recently has assumed that…
Qinguo Liu, Fangzhou Xiao
Biocircuits often realize their functions only within specific parameter regimes, yet identifying those regimes and quantifying how difficult they are to satisfy remain challenging. Powered by the recently developed Reaction Order Polyhedra (ROP) framework enabling a holistic analysis of the behavior in biomolecular…
Authors not listed
Inverse molecular design aims to generate novel chemical structures that satisfy multiple property constraints, yet reinforcement-learning (RL) fine-tuning can be sensitive to how objectives are converted into a scalar reward. Here, we systematically analyze how scalarization choices and stabilization mechanisms shape…
Chmura, Nguyen, Biermann
In an experimental choice situation, we identify risk-acceptability thresholds and show how such thresholds are updated in response to benchmark information, a recurrent feature of health, safety, and environmental (HS&E) risk governance. We present a theoretical framework linking the observed behavior to an underlying…
Martyna Kobus, Radosław Kurek, T.E. Parker
Strong empirical evidence from laboratory experiments, and more recently from population surveys, shows that individuals, when evaluating their situations, pay attention to whether they experience gains or losses, with losses weighing more heavily than gains. The electorate's loss aversion, in turn, influences…
Symeon Vaidanis, Marios Kountouris
In multi-objective and multi-criteria decision-making under risk, especially in settings involving individual behavior, risk-aware analysis based on subjective evaluation has become increasingly important. Moving beyond risk-neutral modeling and the constraints of Expected Utility Theory (EUT), Cumulative Prospect…
Carole Bernard, Silvana M. Pesenti
We introduce a framework for preference-robust decision making when preferences over risk are modelled through generalised distortion risk measures. Unlike distributional robustness, our approach addresses ambiguity in the risk functional itself. We construct ambiguity sets on distortion (weight) functions using the…
Alice N. Ardichvili, Markus Bittlingmaier, Grégoire T. Freschet, Michel Loreau + 1 more
Species diversity potentially has a dual effect on communities: a generally positive effect on overall community biomass, reflecting the expression of species response and interaction traits, and a poorly characterised effect on mass-specific species contribution to ecosystem functions, reflecting the expression of…