Decision making involving imperfect knowledge

1993 ◽  
Vol 23 (3) ◽  
pp. 840-851 ◽  
Author(s):  
C.F. Eick ◽  
N.N. Mehta
Keyword(s):  
Decision Making ◽  
Imperfect Knowledge

Prospects for the open treatment of uncertainty in environmental research

2010 ◽  
Vol 34 (1) ◽  
pp. 75-100 ◽  
Author(s):  
James D. Brown
Keyword(s):  
Decision Making ◽  
Dominant Role ◽  
Scientific Information ◽  
Environmental Modeling ◽  
Environmental Research ◽  
Time Variability ◽  
Sources Of Uncertainty ◽  
Open Treatment ◽  
Imperfect Knowledge

Current treatments of uncertainty in environmental research embody several myths about the causes and consequences of imperfect knowledge, namely: (1) the dominant role of environmental factors in controlling uncertainty, such as system complexity, non-linearity and space-time variability, rather than social and psychological factors; (2) the primacy of observations in locating, quantifying, and reducing uncertainty; and (3) the value of technical assessments of uncertainty in ‘risk-based decision-making’. While the identification and treatment of specific sources of uncertainty remain impractical in some areas of environmental research, a source-based approach is increasingly used in environmental modeling. Here, selected sources of uncertainty are quantified with probability distributions and propagated to model outputs (a forward problem), while data are used to calibrate these estimates and reduce uncertainty (an inverse problem). More generally, current treatments of uncertainty and risk are dominated by attempts to quantify, minimize, and control uncertainty. Uncertainty is viewed as an ‘information deficit’ to be resolved, rather than an inherent product of conducting research. This paper argues for more open treatments of uncertainty in environmental research. Such openness requires an appreciation of the social and psychological causes of uncertainty, the role of observations as imperfect and contingent expressions of visible events, and the myriad ways in which scientific information can be misinterpreted, misused, or sidelined in environmental decision-making. The paper begins with a discussion of the nature and causes of uncertainty in environmental research. A review of current treatments of uncertainty is followed by an analysis of the source-based approach to assessing uncertainty. Prospects for the open treatment of uncertainty are then discussed in terms of circumventing the three ‘myths of uncertainty’ that characterize recent work in environmental research.

scholarly journals Logistics decision-making based on the maturity assessment of imperfect knowledge

2019 ◽  
Vol 11 (4) ◽  
pp. 65-79 ◽  
Author(s):  
Lech Bukowski
Keyword(s):  
Decision Making ◽  
Risk Taking ◽  
System Analysis ◽  
Practical Implication ◽  
Managerial Decision ◽  
Smart Systems ◽  
Theoretical Contribution ◽  
Objective Quality ◽  
Imperfect Knowledge ◽  
Using Data

Abstract The main purpose of this article is to develop a method that allows for an objective quality assessment of imperfect knowledge, which is necessary for decision-making in logistics. The methodology aimed at achieving this goal is established on the system analysis of the entire process employed for obtaining, processing and using data and information as well as the knowledge generated on this basis. The result of this work is a general framework that can be used for managerial decision-making in smart systems that are part of Industry 4.0, and, in particular, Logistics 4.0. A key theoretical contribution of this framework is the concept for quantitative assessment of the maturity of imperfect knowledge acquired from Big Data. The practical implication of this concept is the possibility to use the framework for the assessment of the acceptable risk associated with a managerial decision. For this purpose, the article presents a brief example of how to use this methodology in the risk-taking decision-making process. Finally, the summary and discussion of the results are offered.

scholarly journals Embracing data uncertainty in water decision-making: an application to evaluate water supply and sewerage in Spain

2018 ◽  
Vol 19 (3) ◽  
pp. 778-788 ◽  
Author(s):  
Fatine Ezbakhe ◽  
Agustí Pérez-Foguet
Keyword(s):  
Decision Making ◽  
Confidence Interval ◽  
Water Supply ◽  
Decision Makers ◽  
Data Uncertainty ◽  
Management Decision ◽  
Interval Approach ◽  
Management Decision Making ◽  
Imperfect Knowledge ◽  
Subjective Input

Abstract Analyses of complex water management decision-making problems, involving tradeoffs amongst multiple criteria, are often undertaken using multi-criteria decision analysis (MCDA) techniques. Various forms of uncertainty may arise in the application of MCDA methods, including imprecision, inaccuracy or ill determination of data. The ELECTRE family methods deal with imperfect knowledge of data by incorporating ‘pseudo-criteria’, with discrimination thresholds, to interpret the outranking relation as a fuzzy relation. However, the task of selecting thresholds for each criterion can be difficult and ambiguous for decision-makers. In this paper, we propose a confidence-interval-based approach which aims to reduce the subjective input required by decision-makers. The proposed approach involves defining the uncertainty in the input values using confidence intervals and expressing thresholds as a function of the interval estimates. The usefulness of the approach is illustrated by applying it to evaluate the water supply and sewerage services in Spain. Results show that the confidence interval approach may be interesting in some cases (e.g. when dealing with statistical data from surveys or measuring equipment), but should never replace the preferences or judgments of the actors involved in the decision process.

Discarding optimality: Throwing out the baby with the bathwater?

2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Standard Observer ◽  
Rate Maximization ◽  
Reward Rate Maximization ◽  
Descriptive Standard ◽  
Observer Model

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

LPCD framework: Analytical tool or psychological model?

2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks
Keyword(s):  
Decision Making ◽  
Analytical Tool ◽  
Mathematical Framework ◽  
Bayesian Decision ◽  
Perceptual Decision Making ◽  
Psychological Model ◽  
Psychological Reality ◽  
Psychological Theories ◽  
Target Article ◽  
Bayesian Decision Making

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.

Elaborating the role of reflection and individual differences in the study of folk-economic beliefs

2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Cognitive Processes ◽  
Evolutionary History ◽  
Behavioral Responses ◽  
History Of ◽  
Economic Beliefs

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.

The primacy of conscious decision making – ERRATUM

2014 ◽  
Vol 38 (01) ◽  
pp. 46
Author(s):  
David R. Shanks ◽  
Ben R. Newell
Keyword(s):  
Decision Making ◽  
Conscious Decision

The primacy of conscious decision making – RETRACTION

2014 ◽  
Vol 38 (01) ◽  
pp. 48
Author(s):  
David R. Shanks ◽  
Ben R. Newell
Keyword(s):  
Decision Making ◽  
Conscious Decision

Abstraction: An alternative neurocognitive account of recognition, prediction, and decision making

2020 ◽  
Vol 43 ◽  
Author(s):  
Valerie F. Reyna ◽  
David A. Broniatowski
Keyword(s):  
Decision Making ◽  
Software Engineering ◽  
Systems Engineering ◽  
Evidence Based ◽  
Extensive Literature ◽  
Trace Theory ◽  
Fuzzy Trace Theory ◽  
Abstract Representations ◽  
Technical Systems

Abstract Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and alternative evidence-based conceptions. We draw on conceptions in software engineering, socio-technical systems engineering, and a neurocognitive theory with abstract representations of gist at its core, fuzzy-trace theory.

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