scholarly journals Expected Value of Sample Information For Individual Level Simulation Models To Inform Stop/Go Decision Making By Public Research Funders: A Methodology for The Dafneplus Diabetes Education Cluster Rct

2017 ◽  
Vol 20 (9) ◽  
pp. A776 ◽  
Author(s):  
A Brennan ◽  
D Pollard ◽  
L Coates ◽  
M Strong ◽  
S Heller
foresight ◽  
2014 ◽  
Vol 16 (4) ◽  
pp. 309-328 ◽  
Author(s):  
Evgeniya Lukinova ◽  
Mikhail Myagkov ◽  
Pavel Shishkin

Purpose – This paper aims to study the value of sociality. Recent experimental evidence has brought to light that the assumptions of the Prospect Theory by Kahneman and Tversky do not hold in the proposed substantive domain of “sociality”. In particular, the desire to be a part of the social environment, i.e. the environment where individuals make decisions among their peers, is not contingent on the framing. Evolutionary psychologists suggest that humans are “social animals” for adaptive reasons. However, entering a social relationship is inherently risky. Therefore, it is extremely important to know how much people value “sociality”, when the social outcomes are valued more than material outcomes and what kinds of adaptations people use. Design/methodology/approach – We develop a new theory and propose the general utility function that features “sociality” component. We test the theory in the laboratory experiments carried out in several countries. Findings – Our results suggest that when stakes are low the theory of “sociality” is successful in predicting individual decisions: on average, people do value “sociality” and it surpasses the monetary loss. Originality/value – The main contribution of this paper is the breakdown of the risk attitudes under low stakes and individual level of decision-making. Another advancement is the ability to formalize the social utility or the theory of “sociality” in an economic model; we use general utility function that we define both on the outcomes and on the process of the decision-making itself and test in laboratory studies.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Brian Silston ◽  
Toby Wise ◽  
Song Qi ◽  
Xin Sui ◽  
Peter Dayan ◽  
...  

AbstractNatural observations suggest that in safe environments, organisms avoid competition to maximize gain, while in hazardous environments the most effective survival strategy is to congregate with competition to reduce the likelihood of predatory attack. We probed the extent to which survival decisions in humans follow these patterns, and examined the factors that determined individual-level decision-making. In a virtual foraging task containing changing levels of competition in safe and hazardous patches with virtual predators, we demonstrate that human participants inversely select competition avoidant and risk diluting strategies depending on perceived patch value (PPV), a computation dependent on reward, threat, and competition. We formulate a mathematically grounded quantification of PPV in social foraging environments and show using multivariate fMRI analyses that PPV is encoded by mid-cingulate cortex (MCC) and ventromedial prefrontal cortices (vMPFC), regions that integrate action and value signals. Together, these results suggest humans utilize and integrate multidimensional information to adaptively select patches highest in PPV, and that MCC and vMPFC play a role in adapting to both competitive and predatory threats in a virtual foraging setting.


Author(s):  
Wouter H. Vermeer ◽  
Justin D. Smith ◽  
Uri Wilensky ◽  
C. Hendricks Brown

AbstractPreventing adverse health outcomes is complex due to the multi-level contexts and social systems in which these phenomena occur. To capture both the systemic effects, local determinants, and individual-level risks and protective factors simultaneously, the prevention field has called for adoption of system science methods in general and agent-based models (ABMs) specifically. While these models can provide unique and timely insight into the potential of prevention strategies, an ABM’s ability to do so depends strongly on its accuracy in capturing the phenomenon. Furthermore, for ABMs to be useful, they need to be accepted by and available to decision-makers and other stakeholders. These two attributes of accuracy and acceptability are key components of open science. To ensure the creation of high-fidelity models and reliability in their outcomes and consequent model-based decision-making, we present a set of recommendations for adopting and using this novel method. We recommend ways to include stakeholders throughout the modeling process, as well as ways to conduct model verification, validation, and replication. Examples from HIV and overdose prevention work illustrate how these recommendations can be applied.


2020 ◽  
Vol 70 (1) ◽  
pp. 54-59
Author(s):  
Zhi Zhu ◽  
Yonglin Lei ◽  
Yifan Zhu

Model-driven engineering has become popular in the combat effectiveness simulation systems engineering during these last years. It allows to systematically develop a simulation model in a composable way. However, implementing a conceptual model is really a complex and costly job if this is not guided under a well-established framework. Hence this study attempts to explore methodologies for engineering the development of simulation models. For this purpose, we define an ontological metamodelling framework. This framework starts with ontology-aware system conceptual descriptions, and then refines and transforms them toward system models until they reach final executable implementations. As a proof of concept, we identify a set of ontology-aware modelling frameworks in combat systems specification, then an underwater targets search scenario is presented as a motivating example for running simulations and results can be used as a reference for decision-making behaviors.


Author(s):  
Esmaeel Moradi ◽  
Mohammad Reza Ghezel Arsalan ◽  
Ali Naimi Sadigh ◽  
Hamed Fallah Roshan Ghalb

Moreover, a wide review given by Terzi and Cavalieri (2004) on more than 80 papers about simulation in the supply chain context is used in this chapter. The main goal of this review is to determine which objectives simulation is used to solve the problems, which simulation models are more appropriate and useful for supporting the decision making in the supply chain.


Author(s):  
Randy Borum ◽  
Mary Rowe

Bystanders—those who observe or come to know about potential wrongdoing—are often the best source of preattack intelligence, including indicators of intent and “warning” behaviors. They are the reason that some planned attacks are foiled before they occur. Numerous studies of targeted violence (e.g., mass shootings and school shootings) have demonstrated that peers and bystanders often have knowledge of an attacker’s intentions, concerning communication, and troubling behavior before the attack occurs. This chapter describes—with empirical support—why threat assessment professionals should consider bystanders; outlines a model for understanding bystander decision-making; reviews common barriers to bystander reporting; and suggests ways to mitigate those barriers, to engage bystanders at an individual level, and to improve reporting. The principal aim of threat assessment is to prevent (primarily) intentional acts of harm. When tragic incidents of planned violence occur, however, it is almost always uncovered “that someone knew something” about the attack before it happened. This happens because, as attack plans unfold, people in several different roles may know, or come to know, something about what is happening before harm occurs. The perpetrators know, and so might others, including targets, family members, friends, coworkers, or even casual observers.


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