Resolution Of Uncertainty Research Articles

Ambiguity, randomization and the timing of resolution of uncertainty

Ambiguity, randomization and the timing of resolution of uncertainty

Adjustable robust optimization approach for SVM under uncertainty

The support vector machine (SVM) is one of the successful approaches to the classification problem. Since the values of features are typically affected by uncertainty, it is important to incorporate uncertainty into the SVM formulation. This paper focuses on developing a robust optimization (RO) model for SVM. A key distinction from existing literature lies in the timing of optimizing decision variables. To the best of our knowledge, in all existing RO models developed for SVM, a common assumption is that all decision variables are decided before the uncertainty realization, which leads to an overly conservative decision boundary. However, this paper adopts a different strategy by determining the variables that assess the misclassification error of data points or their fall within the margin post-realization, resulting in a less conservative model. The RO models where decisions are made in two stages (some before and the rest after the uncertainty resolution), are called adjustable RO models. This adjustment results in a three-level optimization model for which two decomposition-based algorithms are proposed. In these algorithms, after providing a bi-level reformulation, the model is divided into a master-problem (MP) and a sub-problem the interaction of which yields the optimal solution. Acceleration of algorithms via incorporating valid inequalities into MP is another novelty of this paper. Computational results over simulated and real-world datasets confirm the efficiency of the proposed model and algorithms.

Inducing inhibition affects propagation of uncertainty and checking behaviors

AbstractDifficulty tolerating uncertainty is a central deficit across psychopathologies, and checking behavior is a common response to uncertainty. Inducing inhibition improves resolution of uncertainty. However, it is unclear whether inducing inhibition improves decision-making under conditions of uncertainty or whether it reduces checking. This study evaluated how inducing inhibition affects resolution of uncertainty and checking separately. Healthy adults (N = 34) completed three experiments combining an inhibition-induction task with a novel visual-matching task, which dissociated resolving uncertainty from checking. In Experiment 1, the visual-matching task included only “certainty” trials with unlimited checking. In Experiment 2, the task featured “certainty” and “uncertainty” trials, without checking. In Experiment 3, the task featured “certainty” trials, without checking. All participants completed self-report assessments of relevant clinical constructs including obsessive-compulsive symptoms and depressive symptoms. Our results indicate that inducing inhibition reduces unnecessary checking in “certainty” trials. Inducing inhibition also improves accuracy in “uncertainty” trials when checking is impossible, by limiting the harmful propagation of uncertainty. The propagation of uncertainty correlated with depressive symptoms and checking correlated with obsessive-compulsive symptoms. Our results offer a novel measure of different uncertainty facets and demonstrate the interactions between inhibition, uncertainty, and checking. We also outline implications for understanding specific uncertainty facets in psychopathologies and suggest that inducing inhibition may play a role in alleviating certain mental health symptoms.

The Value of Information is Context Dependent: A Demonstration of Decision Tools to Address Multispecies River Temperature Management Under Uncertainty

Trade‐offs among objectives in natural resource management can be exacerbated in altered ecosystems and when there is uncertainty in predicted management outcomes. Multi‐criteria decision analysis and value of information (VOI) are underutilized decision tools that can assist fisheries managers in handling trade‐offs and evaluating the importance of uncertainty. We demonstrate the use of these tools using a case study in the Sacramento River, California, USA, where two imperiled species with different temperature requirements, winter‐run Chinook Salmon Oncorhynchus tshawytscha and Green Sturgeon Acipenser medirostris, spawn and rear in the artificially cold Shasta Dam tailwater. A temperature‐control device installed on Shasta Dam maintains cool water for Chinook Salmon; however, uncertainties exist related to the effects of temperatures on the spawning and rearing of both species. We consider four alternative hypotheses in models of early life‐stage dynamics to evaluate the effects of alternative temperature management strategies on Chinook Salmon and Green Sturgeon management objectives. We used VOI to quantify the increase in management performance that can be expected by resolving hypothesis‐based uncertainties as a function of the weight assigned to species‐specific objectives. We found the decision was hindered by uncertainty; the best performing alternative depends on which hypothesis is true, with warmer or cooler alternative management strategies recommended when weights favor Green Sturgeon or Chinook Salmon objectives, respectively. The value of reducing uncertainty was highest when Green Sturgeon was slightly favored, highlighting the interaction between scientific uncertainty and decision makers' values. Our demonstration features multi‐criteria decision analysis and VOI as transparent, deliberative tools that can assist fisheries managers in confronting value conflicts, prioritizing resolution of uncertainty, and optimally managing aquatic ecosystems.

Characterization of photoelastic materials by Mach–Zehnder interferometry: Application to trigonal calcium galogermanate (CGG) crystals

We explore piezooptic and photoelastic properties of Ca3Ga2Ge4O14 (CGG) crystals. A Mach–Zehnder interferometry technique is utilized to determine a complete set of the piezooptic tensor constants πim, with particular attention to the measurement accuracy, reliability, and uncertainty resolution in the piezooptic measurements. For these reasons, independent piezooptic constants or their combinations were determined by performing interferometric measurements for different geometries of piezooptic coupling using samples of both principal (direct) and non-principal (X/45°) crystallographic cuts. Basing on the results of piezooptic measurements, a complete set of photoelastic tensor constants pim and the acousto-optic performance (figure of merit M2) of CGG crystals were evaluated. The obtained piezooptic, photoelastic, and acousto-optic characteristics of CGG crystals are compared with those of other crystals of the langasite group, langasite and CTGS (Ca3TaGa3Si2O14). A comparative analysis reveals a correlation between the values of the piezooptic or photoelastic constants and the lattice parameters for this group of crystals. High optical quality and optical transparency in the UV region of the spectrum up to 260 nm together with extremely high mechanical resistance to uniaxial compression (≤2000 kg/cm2) opens up the possibility for specific application of CGG crystal as an optical material for piezooptic sensors of high uniaxial compression. The presented piezooptic interference technique along with methodological and metrological approaches paves the way for accurate and unambiguous characterization of photoelastic crystal materials of trigonal symmetry.

Accounting and Finance: Complementarity and Divergence

Abstract Penman (2023. Accounting for Uncertainty. Accounting, Economics, and Law: A Convivium) develops a conceptual framework which reconciles accounting and finance in view to provide information for financial investment. His framework is based upon resolution of uncertainty over expectations as a convenient basis for accrual accounting. In this context, accrual accounting can be interpreted as a convenient instrument to protect the corporate capacity to generate future earnings on which the expected financial value is based upon. However, in order to fulfil this control function, accounting applies an additive process (simple return), while financial valuation imposes a multiplicative process (compound return) over the invested financial capital. This divergence between accounting and finance enables disentangling business profit – as determined by accounting – from money interest and ownership rent, paving the way to a theory of the business firm based upon its accounting structure, and enabling measures of financial performance consistent with this divergence.

The influence of uncertainty on indulgent consumption: a chain mediation model of curiosity and positive emotion

PurposePeople usually try to avoid uncertainty. Recently, however, uncertainty has become an emerging marketing tool in the hedonic product industry. In the case of blind box consumption, for example, the consumers become addicted to the uncertainty created by businesses, leading to repeat purchases and even indulgences. Previous research has, yet, to focus on the impact of uncertainty on indulgence and the role of emotions.Design/methodology/approachThis paper constructs and validates a chain mediation model of uncertainty triggering indulgent consumption based on the information gap theory, positive emotion theory and uncertainty resolution theory and examines the difference between resolved and unresolved uncertainty. This study also explores differences in the impact of whether uncertainty is resolved on emotions. The uncertainty-resolved group elicited a more positive emotional response than the uncertainty-unresolved group, leading to a more indulgent consumption.FindingsThe results of three studies show that uncertainty influences indulgent consumption through curiosity and positive emotion, and that curiosity and positive emotion play separate and chain mediating roles between uncertainty and indulgent consumption, respectively. We validate our central hypothesis with questionnaires among blind box consumer groups, examining the moderating role of perceived luck and risk preferences.Originality/valueThe findings shed new light on firms' use of uncertainty to promote consumer purchases.

The sensitivity of risk premiums to the elasticity of intertemporal substitution

AbstractThis paper incorporates reference‐dependent preferences into a consumption‐based asset pricing model featuring Epstein–Zin utility. Three relevant results emerge from this extension. First, agents prefer the late resolution of uncertainty in recursive utility. Second, the late resolution of uncertainty helps replicate the downward‐sloping term structure of market excess return. Third, the intertemporal substitution elasticity is more sensitive to asset prices through increasing precautionary saving motivations. A closed‐form solution for the proposed model largely explains (i) high, volatile, and countercyclical equity premiums; (ii) low risk‐free rates; and (iii) the downward‐sloping term structure of equity premiums and variance ratios.

Does public information facilitate price consensus? Characterizing USDA announcement effects using realized volatility

The provision of public information in commodity markets is justified in part by the idea that public information generates consensus among market participants about the fundamental value of the commodity and reduces price volatility. Significant reductions in options-implied volatility following report releases have been presented as evidence of this market-calming effect. We scrutinize this finding in more detail by comparing implied volatility to realized volatility measures from intraday price data. We show that while implied volatility does indeed fall after report releases, realized volatility does not decrease. We measure realized volatility using intraday data and find evidence of much higher volatility on report days only within minutes of the report release. This pattern is consistent with changes in implied volatility being driven by the resolution of uncertainty about the information contained in the report, rather than changes in volatility expectations that may reflect the consensus among traders about forthcoming price volatility.

Disregarding Uncertainty, Marginalizing Patients

What does it mean to “trust the science”? The phrase is often used to suggest that scientific knowledge is static and that the public can treat current recommendations as eternal verities. The medical community is not omniscient, however. Indeed, some illnesses are characterized by uncertainty: it is not clear with what frequency the associated symptoms occur or whether they are a manifestation of a psychological disorder or a physiological disease. The medical field is no stranger to such challenges, labeling such illnesses as “contested.” The communication of uncertainty surrounding these illnesses, however, presents a troubling dynamic. Rather than engaging in constructive dialogue that moves scientific understanding forward, viewpoints become entrenched, points of disagreement are obscured, and professionals retaliate against one another. In the best case scenario, patients are merely left to sort through dense medical concepts on their own; in the worst case, they are targeted by predatory providers. Patients suffer, trust in science declines.
 Drawing on insights from the economics literature, this Article presents a theoretical framework for approaching the uncertainty inherent in contested illnesses. The framework discusses the pattern of evidence accumulation that accompanies an uncertain illness, distinct from that of a disease where uncertainty is substantially resolved. Applying these insights to the communication of uncertainty surrounding contested illnesses, the Article notes that null results in the presence of well-designed studies should be weighed differently than null results in the presence of case studies or small sample studies. If an illness is truly uncertain, the framework highlights the potential benefits of additional caution in approaching irreversible actions, such as prematurely communicating the resolution of uncertainty (which can lead to the development of patient mistrust). This careful communication of uncertainty is vital to prevent patient marginalization and to clarify the often-inscrutable information landscape in these contexts. Current regulations for medical providers and public figures are insufficient, however, to incentivize such careful communication. This Article proposes a government-coordinated informational digest that weighs existing evidence based on the rigor of study design and imputes null results to missing results of completed studies. The agency coordinating the digest will provide incentives for studies that fill gaps in the literature and which incorporate input from patient advocate groups into the design. In doing so, it will enable the medical community to both better handle existing uncertainty and to take important steps toward resolving it. More importantly, however, this transparent process educates the public about how scientific beliefs should evolve and prevents the irreversible harm of patient marginalization.

Comparative Effectiveness and Safety of Direct Oral Anticoagulants in Low Body Weight Patients with Atrial Fibrillation: A Systematic Review and Meta-analysis.

Direct oral anticoagulant (DOAC) agents are established as the anticoagulation strategy of choice for a variety of clinical risks. Despite this, uncertainty still exists with regard to their efficacy and safety for the prevention of stroke and systemic embolism in some patient populations; most notably those with low body weight (LBW) (<60 kg or body mass index [BMI] <18 kg/m2). Currently, there is a paucity of trial and non-trial data to support a prescriptive recommendation for their use in these patient cohorts. We have carried out a pooled systematic review of the most up to date published data of patients stabilized on various DOAC analogs with the view to ascertaining the exact matrices of their efficacy and safety in these cohorts of patients. We initially carried out a comprehensive search of databases from inception to June 2023 for eligible studies exploring the efficacy and safety of various analogs of direct oral anticoagulants in patients with atrial fibrillation who had low body weight. Databases accessed include PubMed, EMBASE, the Science Citation Index, the Cochrane Database of Systematic Reviews, and the Database of Abstracts of Reviews of Effectiveness. We carried out a weighted comparison of derived pooled odd ratios (with their corresponding confidence intervals) of mortality outcomes between various DOACs using the random effects model. Thirteen studies (n = 165,205 patients) were included in our meta-analysis. DOAC analogs were associated with increased stroke-related events, composite outcome, and mortality in low body weight patients compared to non-low body weight patients (odds ratio [OR] 1.50, 95% confidence interval [CI] 1.17-1.92), (OR 1.55, 95% CI 1.29-1.86), (OR 2.92, 95% CI 1.87-4.58), respectively. There was no significant difference in the safety outcome (major bleeding events) between the DOAC analogs (OR 1.19, 95% CI 0.93-1.52). In this meta-analytical review comprising both real-world and randomized controlled studies, the use of DOAC analogs in low body weight patients (body weight of <60 kg or BMI<18 kg/m2) with atrial fibrillation was associated with increased risks of stroke-related events, composite outcomes, and mortality compared to non-low body weight cohorts patients. At the same time, there was no significant difference in terms of major bleeding events. This finding has provided the first resolution of pervading uncertainty surrounding the use of DOAC analogs in these patient cohorts and suggests the need for follow-up confirmatory systematic studies in this group of patients.

The Resolution of Uncertainty in the Value and Probability Domains

The Resolution of Uncertainty in the Value and Probability Domains

Designing ecosystems of intelligence from first principles

This white paper lays out a vision of research and development in the field of artificial intelligence for the next decade (and beyond). Its denouement is a cyber-physical ecosystem of natural and synthetic sense-making, in which humans are integral participants—what we call “shared intelligence.” This vision is premised on active inference, a formulation of adaptive behavior that can be read as a physics of intelligence, and which inherits from the physics of self-organization. In this context, we understand intelligence as the capacity to accumulate evidence for a generative model of one’s sensed world—also known as self-evidencing. Formally, this corresponds to maximizing (Bayesian) model evidence, via belief updating over several scales, that is, inference, learning, and model selection. Operationally, this self-evidencing can be realized via (variational) message passing or belief propagation on a factor graph. Crucially, active inference foregrounds an existential imperative of intelligent systems; namely, curiosity or the resolution of uncertainty. This same imperative underwrites belief sharing in ensembles of agents, in which certain aspects (i.e., factors) of each agent’s generative world model provide a common ground or frame of reference. Active inference plays a foundational role in this ecology of belief sharing—leading to a formal account of collective intelligence that rests on shared narratives and goals. We also consider the kinds of communication protocols that must be developed to enable such an ecosystem of intelligences and motivate the development of a shared hyper-spatial modeling language and transaction protocol, as a first—and key—step towards such an ecology.

Insurance and the Preference for Early Resolution of Uncertainty

Insurance and the Preference for Early Resolution of Uncertainty

Inequality, premium and the timing of resolution of uncertainty

We incorporate Epstein-Zin preferences in an exchange economy with income uncertainty and examine the effect of inequality on the equity risk premium. When agents have preference for late resolution of uncertainty, inequality increases the premium for low income uncertainty and decreases the premium for large income uncertainty. When agents have preference for early resolution of uncertainty, inequality increases the equity premium even when the level of income uncertainty is large. Our results suggest that the time preference for resolution of uncertainty has an important effect on income uncertainty, which subsequently affects the relationship of inequality with the equity risk premium.

Application research of BP neural network PID in control system of heat exchange station

In the direction of better resolution of time lag, nonlinearity and uncertainty in the heating system, a BPNN-PID (BP neural network PID) controller is proposed in this paper. A complete heating auto-control system is designed with the experimental platform of a university heat exchange station in Zhangjiakou as the research background. The auto-control system takes Programmable Logic Controller (PLC) as the control core, uses BPNN algorithm to optimize the PID control parameters, and finally takes outlet temperature of 1# plate exchanger as the main control parameter to conduct experimental research on BPNN-PID control and single-loop feedback control respectively. The results show that compared with the single-loop feedback controller, the PID control based on BPNN algorithm has superior control quality, with shorter adjustment time, smaller overshoot, finer control accuracy and stability.

Linear switched system modelling and analysis for the servo system

AbstractAiming at resolving the parameter uncertainty of the servo system under multi‐working conditions, a flatness‐based switched linear system model is proposed. Firstly, a fifth‐order linear switched discrete‐time system with uncertain parameters is established. The flatness properties of switched system is described and a de Bruijn's graph‐based framework is introduced for graphical description of the switched system. In addition, non‐linear bode diagrams are obtained via sweeping signals with multiple amplitudes. The discrete equations of the electromechanical servo system are established by the bode plots. The unknown parameters of the subsystems in switched model are identified by the simulated annealing algorithm, and compared with the least squares method to verify the accuracy of the identified parameters. Finally, the simulation model and experimental platform are constructed to verify the effectiveness of the proposed method. The switched model is compared with the classical transfer function model and single subsystems. The results indicate that the resolution of parameter uncertainty in servo systems is effective. The accuracy of the established switched model is about 99.5%. The accuracy of the switched linear system model of the electromechanical servo system is verified and the proposed modelling method is validated.

Non-instrumental information seeking is resistant to acute stress

Previous research has shown that people intrinsically value non-instrumental information, which cannot be used to change the outcome of events, but only provides an early resolution of uncertainty. This is true even for information about rather inconsequential events, such as the outcomes of small lotteries. Here we investigated whether participants’ willingness to pay for non-instrumental information about the outcome of simple coin-flip lotteries with guaranteed winnings was modulated by acute stress. Stress was induced using the Socially Evaluated Cold Pressor Test (SECPT), and information-seeking choices were compared to a warm water control group. Our results neither support the hypothesis that stress decreases information-seeking by directing cognitive resources away from the relevance of the lotteries, nor the opposite hypothesis that stress increases information-seeking by driving anxiety levels up. Instead, we found that despite successful stress induction, as evidenced by increased saliva cortisol levels in the SECPT group, information valuation was remarkably stable. This finding is in line with recent findings that experimentally increased state anxiety did not modulate non-instrumental information seeking. Together, these results suggest that the aversiveness of “not knowing” is a stable cognitive state and not easily modulated by situational context, such as acute stress.

Informing Program Management Decisions Using Quantitative Set-Based Design

System design is an exercise in sequential decision-making, with the objective of developing resilient and affordable systems. Throughout the design process, engineering and program managers must balance several competing objectives, such as ensuring design feasibility, minimizing cost, schedule, and performance risk, while simultaneously achieving stakeholder value. Thus, engineering and program managers require design and analysis methods enabling complex and multiobjective design decisions under uncertainty. Unfortunately, there exists limited research providing quantitative methodologies specifically enabling program management decisions using quantitative set-based design. We, therefore, present a quantitative set maturation and uncertainty resolution decision methodology using value-focused multiobjective decision models and model-based engineering practices. This methodology assesses and quantifies uncertainty regarding stakeholder value, cost, requirements, and design maturity for each design set. These metrics facilitate the calculation of the program manager value, which when combined with design set feasibility entropy, enable tradeoff analysis informing design maturation and uncertainty resolution prioritization decisions. We develop and demonstrate our methodology using a model-based unmanned aerial vehicle case study implemented in the ModelCenter modeling environment. This methodology provides program managers an efficient, cost effective, and defensible approach to inform system design maturation and uncertainty resolution decisions enabling the development of resilient and affordable systems.

Flight to Lottery Ahead of FOMC Announcements: Institutional Investors or Retail Investors?

AbstractThis paper studies the pre‐Federal Open Market Committee (FOMC) announcement drift at the stock level. We hypothesize that investors have a higher propensity to speculate before the monetary policy announcements by the FOMC, due to the resolution of uncertainty and associated reduction in investors' fear. Indeed, we find evidence that there exists a drift of lottery‐like stocks in the pre‐FOMC window, when investors' fear gauge is lower, together with higher demand for lottery‐like stocks and higher realized skewness. Moreover, we show that the demand for lottery‐like stocks ahead of FOMC announcements is more prominent among institutional investors than retail investors. Our findings also identify the key role of transient and quasi‐index institutional investors in our documented flight‐to‐lottery effect. Our findings advance the ongoing debates about the role of firms' investor heterogeneity in determining how monetary policy affects corporate managers' decisions. Our paper has important implications for central banks and managers by showing that investors' preference for lottery‐like stocks increases before FOMC announcements.