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\"Knight (1921) defines uncertainty as an informational market failure that, while being detrimental to most existing businesses, presents possible profitable opportunities for others. This book builds upon that classic work by providing an analysis of the alternative approaches to strategic decision-making under such uncertainty. It covers what uncertainty is, why it is important, and what connections it has to business and related fields, culminating in a new and comprehensive typology and a valuable guide for how to appropriately address various types of uncertainties, even under AI. It clarifies the current terminological and categorical confusion about 'unknowns' while complementing the mathematical, probability-based approaches that treat uncertainty as 'knowable' (i.e., as risk). It corrects the mistaken approaches that treat 'unknowables' as 'shapeable' or 'discoverable'. This book widens the perspective for viewing uncertainty, in terms of its impacts across humanity, by offering a shrewder understanding of what roles uncertainties play in human activity. It will appeal to academics across business, economics, philosophy, and other disciplines looking for approaches to apply, test, and hone for dealing with decision-making under uncertainty.\" -- Provided by publisher.

This book explores and formulates the principles necessary for forecasting the economic processes and decision-making under uncertainty. It presents the minimal uncertainty interval to solve the issue of inflexible programs.

In the past, control systems for automation and robotics and the expert systems employed in artificial intelligence were generally based on classical, or Boolean, logic. However, this proved to be inadequate by virtue of its binary nature, for portraying the uncertainties and inconsistencies of the 'real' world, and so from the late 1990s, research has been ongoing into the application of paraconsistent, or non-classical logics in these fields. This book aggregates much of this research, from 1999 up to the present. Organized to facilitate an understanding of the theory and the development of the applied methods, \"Uncertainty Treatment Using Praconsistent Logic\" presents the material in a sequential fashion and is divided into three parts. Notions of Paraconsistent Annotated Logic (PAL) summarizes the basic theory and fundamentals of the subject. The second part, Paraconsistent Analysis Networks (PANets), describes the utilization of paraconsistent logic in constructing networks which can deal with representative data from uncertain information. The final section, Paraconsistent Artificial Neural Networks (PANNets), is composed of six chapters which chart the applications of PAL, from a comparison between Paraconsistent Analysis Nodes (PANs) and the action of the human brain through to complex PANNet architecture capable of processing signals inspired by human brain function. This invaluable state-of-the-art overview will be of interest to all those involved with the development of robotics or artificial intelligence and will serve as reference for future application of paraconsistent logics in all computer and electronic systems.

A guide to the various models and methods to multicriteria decision-making in conditions of uncertainty presented in a systematic approach Multicriteria Decision-Making under Conditions of Uncertainty presents approaches that help to answer the fundamental questions at the center of all decision-making problems: \"What to do?\" and \"How to do it?\" The book explores methods of representing and handling diverse manifestations of the uncertainty factor and a multicriteria nature of problems that can arise in system design, planning, operation, and control. The authors—noted experts on the topic—and their book covers essential questions, including notions and fundamental concepts of fuzzy sets, models and methods of multiobjective as well as multiattribute decision-making, the classical approach to dealing with uncertainty of information and its generalization for analyzing multicriteria problems in condition of uncertainty, and more. This comprehensive book contains information on \"harmonious solutions\" in multiobjective problem-solving (analyzing X, F> models), construction and analysis of X, R > models, results aimed at generating robust solutions in analyzing multicriteria problems under uncertainty, and more. In addition, the book includes illustrative examples of various applications, including real-world case studies related to the authors' various industrial projects. This important resource: * Explains the design and processing aspect of fuzzy sets, including construction of membership functions, fuzzy numbers, fuzzy relations, aggregation operations, and fuzzy sets transformations * Describes models of multiobjective decision-making ( X. M > models), their analysis on the basis of using the Bellman-Zadeh approach to decision-making in a fuzzy environment, and their diverse applications, including multicriteria allocation of resources * Investigates models of multiattribute decision-making ( X, R > models) and their analysis on the basis of the construction and processing of fuzzy preference relations as well as demonstrating their applications to solve diverse classes of multiattribute problems * Explores notions of payoff matrices and fuzzy-set-based generalization and modification of the classic approach to decision-making under conditions of uncertainty to generate robust solutions in analyzing multicriteria problems Written for students, researchers and practitioners in disciplines in which decision-making is of paramount relevance, Multicriteria Decision-Making under Conditions of Uncertainty presents a systematic and current approach that encompasses a range of models and methods as well as new applications.

Balancing the solution-quality/time trade-off and optimizing problems which feature offline and online phases can deliver significant improvements in efficiency and budget control.Offline/online integration yields benefits by achieving high quality solutions while reducing online computation time.

With the increasing role of economic uncertainty, improving the efficiency of forecasts is ever so important. This book makes suggestions on how to evaluate the key economic indicators under uncertainty. It presents the interval method to study economic indicators, which will allow us to understand the possibilities of forecasting and the irregular nature of the economy. It is shown that with the accumulation of negative phenomena in a seemingly stable situation the effect of a compressed spring may snap into action. The book outlines the uncertainty relations in the economy, the minimal uncertainty interval, the effect of an expanding uncertainty band, sensitivity thresholds, as well as the principles of systematization and forecasting of economic indicators. The book presents ways to facilitate economic development, assess the quality of a forecast, and increase the efficiency of forecasts and decision-making in conditions of uncertainty.

This timely book provides a comprehensive, multi-dimensional and comparative analysis of political uncertainty.It is innovative in introducing the notions of inter-institutional, verbally induced, and historical uncertainty.

Sociological practitioners often face considerable methodological uncertainty when undertaking a quantitative analysis. This methodological uncertainty encompasses both data construction (e.g. defining variables) and analysis (e.g. selecting and specifying a modelling procedure). Methodological uncertainty can lead to results that are fragile and arbitrary. Yet, many practitioners may be unaware of the potential scale of methodological uncertainty in quantitative analysis, and the recent emergence of techniques for addressing it. Recent proposals for ‘multi-strategy’ approaches seek to identify and manage methodological uncertainty in quantitative analysis. We present a case-study of a multi-strategy analysis, applied to the problem of estimating the long-term impact of 1980s UK government-sponsored youth training. We use this case study to further highlight the problem of cumulative methodological fragilities in applied quantitative sociology and to discuss and help develop multi-strategy analysis as a tool to address them.

Uncertainties are pervasive in natural hazards, and it is crucial to develop robust and meaningful approaches to characterize and communicate uncertainties to inform modeling efforts. In this monograph we provide a broad, cross-disciplinary overview of issues relating to uncertainties faced in natural hazard and risk assessment. We introduce some basic tenets of uncertainty analysis, discuss issues related to communication and decision support, and offer numerous examples of analyses and modeling approaches that vary by context and scope. Contributors include scientists from across the full breath of the natural hazard scientific community, from those in real-time analysis of natural hazards to those in the research community from academia and government. Key themes and highlights include: Substantial breadth and depth of analysis in terms of the types of natural hazards addressed, the disciplinary perspectives represented, and the number of studies included Targeted, application-centered analyses with a focus on development and use of modeling techniques to address various sources of uncertainty Emphasis on the impacts of climate change on natural hazard processes and outcomes Recommendations for cross-disciplinary and science transfer across natural hazard sciences This volume will be an excellent resource for those interested in the current work on uncertainty classification/quantification and will document common and emergent research themes to allow all to learn from each other and build a more connected but still diverse and ever growing community of scientists.Read an interview with the editors to find out more:https://eos.org/editors-vox/reducing-uncertainty-in-hazard-prediction

Afterlives of Endor offers an analysis of the way early modern English literature addressed the period's anxieties about witchcraft and theatricality. What determined whether or not a demonologist imagined a trial as a spectacle? What underlying epistemological constraints governed such choices and what conceptions of witchcraft did these choices reveal? Pairing readings of demonological texts with canonical plays and poetry, Laura Levine examines such questions. Through analyses of manuals and pamphlets about the prosecution of witches-including Reginald Scot's skeptical The Discoverie of Witchcraft (1584), King James VI/I's Daemonologie (1597), and Jean Bodin's De la Demonomanie des Sorciers (1580)-Afterlives of Endor examines the way literary texts such as Shakespeare's The Winter's Tale and The Tempest , Spenser's The Faerie Queene , and Marlowe's Tragicall History of Doctor Faustus address anxieties about witchcraft, illusion, and theatricality. Afterlives of Endor attends to the rhetorical tactics, argumentative investments, and underlying tensions of demonological texts with the scrutiny ordinarily reserved for literary texts.