Search results for 'Uncertainty' (try it on Scholar)

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  1.  49
    John Pittard & Alex Worsnip (forthcoming). Metanormative Contextualism and Normative Uncertainty. Mind.
    We offer a new argument in favor of metanormative contextualism, the thesis that the semantic value of a normative ‘ought’ claim of the form ‘S ought to Φ’ depends on the value of one or more parameters whose values vary in a way that is determined by the context of utterance. The debate over this contextualist thesis has centered on cases that involve ‘ought’ claims made in the face of uncertainty regarding certain descriptive facts. Contextualists, relativists, and invariantists (...)
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  2. Alessandro Giordani & Luca Mari (2014). Modeling Measurement: Error and Uncertainty. In Marcel Boumans, Giora Hon & Arthur Petersen (eds.), Error and Uncertainty in Scientific Practice. Pickering & Chatto 79-96.
    In the last few decades the role played by models and modeling activities has become a central topic in the scientific enterprise. In particular, it has been highlighted both that the development of models constitutes a crucial step for understanding the world and that the developed models operate as mediators between theories and the world. Such perspective is exploited here to cope with the issue as to whether error-based and uncertainty-based modeling of measurement are incompatible, and thus alternative with (...)
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  3.  90
    Charlie Kurth (2016). Anxiety, Normative Uncertainty, and Social Regulation. Biology and Philosophy 31 (1):1-21.
    Emotion plays an important role in securing social stability. But while emotions like fear, anger, and guilt have received much attention in this context, little work has been done to understand the role that anxiety plays. That’s unfortunate. I argue that a particular form of anxiety—what I call ‘practical anxiety’—plays an important, but as of yet unrecognized, role in norm-based social regulation. More specifically, it provides a valuable form of metacognition, one that contributes to social stability by (...)
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  4. J. Smith, W. Shields & D. Washburn (2003). The Comparative Psychology of Uncertainty Monitoring and Metacognition. Behavioral and Brain Sciences 26 (3):317-339.
    Researchers have begun to explore animals' capacities for uncertainty monitoring and metacognition. This exploration could extend the study of animal self-awareness and establish the relationship of self-awareness to other-awareness. It could sharpen descriptions of metacognition in the human literature and suggest the earliest roots of metacognition in human development. We summarize research on uncertainty monitoring by humans, monkeys, and a dolphin within perceptual and metamemory tasks. We extend phylogenetically the search for metacognitive capacities by considering studies that have (...)
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  5.  71
    Meg Stalcup (2015). Policing Uncertainty: On Suspicious Activity Reporting. In Rabinow Simimian-Darash (ed.), Modes of Uncertainty: Anthropological Cases. University of Chicago 69-87.
    A number of the men who would become the 9/11 hijackers were stopped for minor traffic violations. They were pulled over by police officers for speeding or caught by random inspection without a driver’s license. For United States government commissions and the press, these brushes with the law were missed opportunities. For some police officers though, they were of personal and professional significance. These officers replayed the incidents of contact with the 19 men, which lay bare the uncertainty (...)
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  6.  2
    Susan L. Joslyn & Jared E. LeClerc (2016). Climate Projections and Uncertainty Communication. Topics in Cognitive Science 8 (1):222-241.
    Lingering skepticism about climate change might be due in part to the way climate projections are perceived by members of the public. Variability between scientists’ estimates might give the impression that scientists disagree about the fact of climate change rather than about details concerning the extent or timing. Providing uncertainty estimates might clarify that the variability is due in part to quantifiable uncertainty inherent in the prediction process, thereby increasing people's trust in climate projections. This hypothesis (...)
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  7.  36
    Tomasz Żuradzki (2014). Moral Uncertainty in Bioethical Argumentation: A New Understanding of the Pro-Life View on Early Human Embryos. Theoretical Medicine and Bioethics 35 (6):441-457.
    In this article, I present a new interpretation of the pro-life view on the status of early human embryos. In my understanding, this position is based not on presumptions about the ontological status of embryos and their developmental capabilities but on the specific criteria of rational decisions under uncertainty and on a cautious response to the ambiguous status of embryos. This view, which uses the decision theory model of moral reasoning, promises to reconcile the uncertainty about the ontological (...)
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  8.  1
    Mirta Galesic, Astrid Kause & Wolfgang Gaissmaier (2016). A Sampling Framework for Uncertainty in Individual Environmental Decisions. Topics in Cognitive Science 8 (1):242-258.
    Decisions in the environmental and in particular the climate domain are burdened with uncertainty. Here, we focus on uncertainties faced by individuals when making decisions about environmental behavior, and we use the statistical sampling framework to develop a classification of different sources of uncertainty they encounter. We then map these sources to different public policy strategies aiming to help individuals cope with uncertainty when making environmental decisions.
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  9.  32
    Teddy Seidenfeld, Mark J. Schervish & Joseph B. Kadane (2010). Coherent Choice Functions Under Uncertainty. Synthese 172 (1):157 - 176.
    We discuss several features of coherent choice functions —where the admissible options in a decision problem are exactly those that maximize expected utility for some probability/utility pair in fixed set S of probability/utility pairs. In this paper we consider, primarily, normal form decision problems under uncertainty—where only the probability component of S is indeterminate and utility for two privileged outcomes is determinate. Coherent choice distinguishes between each pair of sets of probabilities regardless the “shape” or “connectedness” of the (...)
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  10. Maurice A. De Gosson (2009). The Symplectic Camel and the Uncertainty Principle: The Tip of an Iceberg? [REVIEW] Foundations of Physics 39 (2):194-214.
    We show that the strong form of Heisenberg’s inequalities due to Robertson and Schrödinger can be formally derived using only classical considerations. This is achieved using a statistical tool known as the “minimum volume ellipsoid” together with the notion of symplectic capacity, which we view as a topological measure of uncertainty invariant under Hamiltonian dynamics. This invariant provides a right measurement tool to define what “quantum scale” is. We take the opportunity to discuss the principle of the symplectic (...)
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  11.  73
    Antonio Di Domenico, Andreas Gabriel, Beatrix C. Hiesmayr, Florian Hipp, Marcus Huber, Gerd Krizek, Karoline Mühlbacher, Sasa Radic, Christoph Spengler & Lukas Theussl (2012). Heisenberg's Uncertainty Relation and Bell Inequalities in High Energy Physics. Foundations of Physics 42 (6):778-802.
    An effective formalism is developed to handle decaying two-state systems. Herewith, observables of such systems can be described by a single operator in the Heisenberg picture. This allows for using the usual framework in quantum information theory and, hence, to enlighten the quantum features of such systems compared to non-decaying systems. We apply it to systems in high energy physics, i.e. to oscillating meson–antimeson systems. In particular, we discuss the entropic Heisenberg uncertainty relation for observables measured at different times (...)
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  12.  72
    Paul Égré & Denis Bonnay (2010). Vagueness, Uncertainty and Degrees of Clarity. Synthese 174 (1):47 - 78.
    In this paper we compare different models of vagueness viewed as a specific form of subjective uncertainty in situations of imperfect discrimination. Our focus is on the logic of the operator “clearly” and on the problem of higher-order vagueness. We first examine the consequences of the notion of intransitivity of indiscriminability for higher-order vagueness, and compare several accounts of vagueness as inexact or imprecise knowledge, namely Williamson’s margin for error semantics, Halpern’s two-dimensional semantics, and the system we call Centered (...)
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  13.  72
    Ralph Wedgwood (2013). Akrasia and Uncertainty. Organon F: Medzinárodný Časopis Pre Analytickú Filozofiu 20 (4):483–505.
    According to John Broome, akrasia consists in a failure to intend to do something that one believes one ought to do, and such akrasia is necessarily irrational. In fact, however, failing to intend something that one believes one ought to do is only guaranteed to be irrational if one is certain of a maximally detailed proposition about what one ought to do; if one is uncertain about any part of the full story about what one ought to do, it could (...)
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  14.  75
    Ron Aboodi, Adi Borer & and David Enoch (2008). Deontology, Individualism, and Uncertainty, a Reply to Jackson and Smith. Journal of Philosophy 105 (5):259-272.
    How should deontological theories that prohibit actions of type K — such as intentionally killing an innocent person — deal with cases of uncertainty as to whether a particular action is of type K? Frank Jackson and Michael Smith, who raise this problem in their paper "Absolutist Moral Theories and Uncertainty" (2006), focus on a case where a skier is about to cause the death of ten innocent people — we don’t know for sure whether on (...)
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  15. Roger M. Cooke (1991). Experts in Uncertainty: Opinion and Subjective Probability in Science. Oxford University Press.
    This book is an extensive survey and critical examination of the literature on the use of expert opinion in scientific inquiry and policy making. The elicitation, representation, and use of expert opinion is increasingly important for two reasons: advancing technology leads to more and more complex decision problems, and technologists are turning in greater numbers to "expert systems" and other similar artifacts of artificial intelligence. Cooke here considers how expert opinion is being used today, how an expert's uncertainty is (...)
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  16.  2
    Arthur Petersen (2014). Uncertainty and God: A Jamesian Pragmatist Approach to Uncertainty and Ignorance in Science and Religion. Zygon 49 (4):808-828.
    This article picks up from William James's pragmatism and metaphysics of experience, as expressed in his “radical empiricism,” and further develops this Jamesian pragmatist approach to uncertainty and ignorance by connecting it to phenomenological thought. The Jamesian pragmatist approach avoids both a “crude naturalism” and an “absolutist rationalism,” and allows for identification of intimations of the sacred in both scientific and religious practices—which all, in their respective ways, try to make sense of a complex world. Analogous to religious (...)
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  17.  3
    Sabine Roeser (2014). The Unbearable Uncertainty Paradox. Metaphilosophy 45 (4-5):640-653.
    People can be risk seeking and risk averse, but people can also be uncertainty averse: in other words, if risk is at least the possibility of an unwanted affect, then it is not only the unwanted effect that they want to avoid, it can also be the uncertainty inherent in the possibility that they wish to avoid. This uncertainty aversion can even lead to a state where someone prefers a certain outcome at all costs, (...)
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  18.  21
    Regula Valérie Burri (2007). Deliberating Risks Under Uncertainty: Experience, Trust, and Attitudes in a Swiss Nanotechnology Stakeholder Discussion Group. NanoEthics 1 (2):143-154.
    Scientific knowledge has not stabilized in the current, early, phase of research and development of nanotechnologies creating a challenge to ‘upstream’ public engagement. Nevertheless, the idea that the public should be involved in deliberative discussions and assessments of emerging technologies at this early stage is widely shared among governmental and nongovernmental stakeholders. Many forums for public debate including focus groups, and citizen juries, have thus been organized to explore public opinions on nanotechnologies in a variety of countries over the past (...)
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  19.  5
    Patrick Suppes (forthcoming). Qualitative Axioms of Uncertainty as a Foundation for Probability and Decision-Making. Minds and Machines:1-18.
    Although the concept of uncertainty is as old as Epicurus’s writings, and an excellent quantitative theory, with entropy as the measure of uncertainty having been developed in recent times, there has been little exploration of the qualitative theory. The purpose of the present paper is to give a qualitative axiomatization of uncertainty, in the spirit of the many studies of qualitative comparative probability. The qualitative axioms are fundamentally about the uncertainty of (...)
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  20.  32
    Tony Gardner-Medwin (2011). Reasonable Doubt : Uncertainty in Education, Science and Law. In Philip Dawid, William Twining & Mimi Vasilaki (eds.), Evidence, Inference and Enquiry. OUP/British Academy 465-483.
    The use of evidence to resolve uncertainties is key to many endeavours, most conspicuously science and law. Despite this, the logic of uncertainty is seldom taught explicitly, and often seems misunderstood. Traditional educational practice even fails to encourage students to identify uncertainty when they express knowledge, though mark schemes that reward the identification of reliable and uncertain responses have long been shown to encourage more insightful understanding. In our information-rich society the ability to identify (...) is often more important than the possession of knowledge itself. In both science and law there are fundamentally different kinds of uncertainty at issue. There is uncertainty whether a particular hypothesis is correct, and there is uncertainty about observable data that may be generated if a particular hypothesis is correct. Both are expressed in terms of probabilities. Each has its own domain of application and its own logic, but the inter-relationship is complex and sometimes misunderstood. Hypothesis probabilities are always open to error through possible failure to take account of realistic alternatives, while the proper inferences that can be drawn from data probabilities (often in the context of significance testing) are quite limited and easily over-interpreted. When considering these two kinds of probability in a court of law it is possible to interpret the phrase 'reasonable doubt' in different ways. It can be seen as addressing data uncertainty: whether such incriminating evidence might with reasonable probability arise to confront an innocent person. Or (the more conventional view) it can be seen as some sort of threshold level on the probability that the defendant is guilty (a hypothesis probability). Each typically involves elements of subjective judgement, but fewer issues and uncertainties arise when considering the data probability and it is argued that this is often the more critical and proper issue for a jury to address. This has particular repercussions for cases involving identification of a suspect through trawl of a DNA or other database. (shrink)
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  21.  96
    Jean E. Burns (2012). The Action of Consciousness and the Uncertainty Principle. Journal of Nonlocality 1 (1).
    The term action of consciousness is used to refer to an influence, such as psychokinesis or free will, that produces an effect on matter that is correlated to mental intention, but not completely determined by physical conditions. Such an action could not conserve energy. But in that case, one wonders why, when highly accurate measurements are done, occasions of non-conserved energy (generated perhaps by unconscious PK) are not detected. A possible explanation is that actions of consciousness take place within the (...)
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  22.  5
    Louise Cummings (2002). Reasoning Under Uncertainty: The Role of Two Informal Fallacies in an Emerging Scientific Inquiry. Informal Logic 22 (2).
    lt is now commonplace in fallacy inquiry for many of the traditional informal fallacies to be viewed as reasonable or nonfallacious modes of argument. Central to this evaluative shift has been the attempt to examine traditional fallacies within their wider contexts of use. However, this pragmatic turn in fallacy evaluation is still in its infancy. The true potential of a contextual approach in the evaluation of the fallacies is yet to be explored. I examine how, in the context of scientific (...)
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  23.  20
    Sven Ove Hansson (2006). Uncertainty and the Ethics of Clinical Trials. Theoretical Medicine and Bioethics 27 (2):149-167.
    A probabilistic explication is offered of equipoise and uncertainty in clinical trials. In order to be useful in the justification of clinical trials, equipoise has to be interpreted in terms of overlapping probability distributions of possible treatment outcomes, rather than point estimates representing expectation values. Uncertainty about treatment outcomes is shown to be a necessary but insufficient condition for the ethical defensibility of clinical trials. Additional requirements are proposed for the nature of that uncertainty. (...)
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  24.  2
    H. Fakhri & M. Sayyah-Fard (forthcoming). An Uncertainty Relation for the Orbital Angular Momentum Operator. Foundations of Physics:1-12.
    A common reducible representation space of the Lie algebras su and su is equipped with two different types of scalar products. The representation bases are labeled by the azimuthal and magnetic quantum numbers. The generators of su are the x-, y- and z-components of the orbital angular momentum operator. The representation of each of these Lie algebras is unitary with respect to only one of the scalar products. To each positive magnetic quantum number a family of the su-Barut–Girardello coherent states (...)
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  25.  6
    Kevin A. Smith & Edward Vul (2013). Sources of Uncertainty in Intuitive Physics. Topics in Cognitive Science 5 (1):185-199.
    Recent work suggests that people predict how objects interact in a manner consistent with Newtonian physics, but with additional uncertainty. However, the sources of uncertainty have not been examined. In this study, we measure perceptual noise in initial conditions and stochasticity in the physical model used to make predictions. Participants predicted the trajectory of a moving object through occluded motion and bounces, and we compared their behavior to an ideal observer model. We found that human judgments (...)
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  26.  52
    John Lemons, Kristin Shrader-Frechette & Carl Cranor (1997). The Precautionary Principle: Scientific Uncertainty and Type I and Type II Errors. [REVIEW] Foundations of Science 2 (2):207-236.
    We provide examples of the extent and nature of environmental and human health problems and show why in the United States prevailing scientific and legal burden of proof requirements usually cannot be met because of the pervasiveness of scientific uncertainty. We also provide examples of how may assumptions, judgments, evaluations, and inferences in scientific methods are value-laden and that when this is not recognized results of studies will appear to be more factual and value-neutral than warranted. Further, we show (...)
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  27.  62
    Jorge Wagensberg (2000). Complexity Versus Uncertainty: The Question of Staying Alive. [REVIEW] Biology and Philosophy 15 (4):493-508.
    Some real objects show a very particular tendency: that of becomingindependent with regard to the uncertainty of their surroundings. This isachieved by the exchange of three quantities: matter, energy andinformation. A conceptual framework, based on both Non-equilibriumThermodynamic and the Mathematical Theory of Communication is proposedin order to review the concept of change in living individuals. Three mainsituations are discussed in this context: passive independence inconnection with resistant living forms (such as seeds, spores, hibernation,...), active independence in connection with (...)
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  28.  15
    Carlotta Piscopo & Mauro Birattari (2008). The Metaphysical Character of the Criticisms Raised Against the Use of Probability for Dealing with Uncertainty in Artificial Intelligence. Minds and Machines 18 (2):273-288.
    In artificial intelligence (AI), a number of criticisms were raised against the use of probability for dealing with uncertainty. All these criticisms, except what in this article we call the non-adequacy claim, have been eventually confuted. The non-adequacy claim is an exception because, unlike the other criticisms, it is exquisitely philosophical and, possibly for this reason, it was not discussed in the technical literature. A lack of clarity and understanding of this claim had a major impact on AI. (...)
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  29.  11
    Aldo Montesano (2008). Effects of Uncertainty Aversion on the Call Option Market. Theory and Decision 65 (2):97-123.
    This article examines the effects of uncertainty aversion in competitive call option markets using a partial equilibrium model with the Choquet-expected utility setup. We find that the trading volume of a call option is negatively affected by uncertainty aversion, whereas the price of the call is practically independent of it.
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  30.  29
    Anne Ingeborg Myhr & Terje Traavik (2002). The Precautionary Principle: Scientific Uncertainty and Omitted Research in the Context of GMO Use and Release. [REVIEW] Journal of Agricultural and Environmental Ethics 15 (1):73-86.
    Commercialization of genetically modified organisms (GMOs) have sparked profound controversies concerning adequate approaches to risk regulation. Scientific uncertainty and ambiguity, omitted research areas, and lack of basic knowledge crucial to risk assessmentshave become apparent. The objective of this article is to discuss the policy and practical implementation of the Precautionary Principle. A major conclusion is that the void in scientific understanding concerning risks posed by secondary effects and the complexity ofcause-effect relations warrant further research. Initiatives to approach the (...)
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  31.  4
    Gitte Meyer, Anna Paldam Folker, Rikke Bagger Jørgensen, Martin Krayer von Krauss, Peter Sandøe & Geir Tveit (2005). The Factualization of Uncertainty: Risk, Politics, and Genetically Modified Crops – a Case of Rape. [REVIEW] Agriculture and Human Values 22 (2):235-242.
    Mandatory risk assessment is intended to reassure concerned citizens and introduce reason into the heated European controversies on genetically modified crops and food. The authors, examining a case of risk assessment of genetically modified oilseed rape, claim that the new European legislation on risk assessment does nothing of the sort and is not likely to present an escape from the international deadlock on the use of genetic modification in agriculture and food production. The new legislation is likely to stimulate the (...)
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  32.  47
    Alessandro Giordani & Luca Mari (2012). Measurement, Models, and Uncertainty. IEEE Transactions on Instrumentation and Measurement 61 (8):2144 - 2152.
    Against the tradition, which has considered measurement able to produce pure data on physical systems, the unavoidable role played by the modeling activity in measurement is increasingly acknowledged, particularly with respect to the evaluation of measurement uncertainty. This paper characterizes measurement as a knowledge-based process and proposes a framework to understand the function of models in measurement and to systematically analyze their influence in the production of measurement results and their interpretation. To (...)
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  33.  6
    Haiyan Xu, Keith W. Hipel, D. Marc Kilgour & Ye Chen (2010). Combining Strength and Uncertainty for Preferences in the Graph Model for Conflict Resolution with Multiple Decision Makers. Theory and Decision 69 (4):497-521.
    A hybrid preference framework is proposed for strategic conflict analysis to integrate preference strength and preference uncertainty into the paradigm of the graph model for conflict resolution (GMCR) under multiple decision makers. This structure offers decision makers a more flexible mechanism for preference expression, which can include strong or mild preference of one state or scenario over another, as well as equal preference. In addition, preference between two states can be uncertain. The result is a preference framework that (...)
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  34.  42
    Lisa Warenski (2012). Relative Uncertainty in Term Loan Projection Models: What Lenders Could Tell Risk Managers. Journal of Experimental and Artificial Intelligence 24 (4):501-511.
    This article examines the epistemology of risk assessment in the context of financial modelling for the purposes of making loan underwriting decisions. A financing request for a company in the paper and pulp industry is considered in some detail. The paper and pulp industry was chosen because it is subject to some specific risks that have been identified and studied by bankers, investors and managers of paper and pulp companies and certain features of the industry enable analysts to quantify the (...)
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  35.  4
    Louise Cummings (2009). Emerging Infectious Diseases: Coping with Uncertainty. [REVIEW] Argumentation 23 (2):171-188.
    The world’s scientific community must be in a state of constant readiness to address the threat posed by newly emerging infectious diseases. Whether the disease in question is SARS in humans or BSE in animals, scientists must be able to put into action various disease containment measures when everything from the causative pathogen to route(s) of transmission is essentially uncertain. A robust epistemic framework, which will inform decision-making, is required under such conditions of uncertainty. I will argue that this (...)
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  36.  24
    Boudewijn de Bruin (2008). Common Knowledge of Payoff Uncertainty in Games. Synthese 163 (1):79-97.
    Using epistemic logic, we provide a non-probabilistic way to formalise payoff uncertainty, that is, statements such as ‘player i has approximate knowledge about the utility functions of player j.’ We show that on the basis of this formalisation common knowledge of payoff uncertainty and rationality (in the sense of excluding weakly dominated strategies, due to Dekel and Fudenberg (1990)) characterises a new solution concept we have called ‘mixed iterated strict weak dominance.’.
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  37.  7
    Anna Paldam Folker & Peter Sandøe (2008). Leaping “Out of the Doubt”—Nutrition Advice: Values at Stake in Communicating Scientific Uncertainty to the Public. Health Care Analysis 16 (2):176-191.
    This article deals with scientific advice to the public where the relevant science is subject to public attention and uncertainty of knowledge. It focuses on a tension in the management and presentation of scientific uncertainty between the uncertain nature of science and the expectation that scientific advisers will provide clear public guidance. In the first part of the paper the tension is illustrated by the presentation of results from a recent interview study with nutrition scientists in (...)
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  38.  35
    William L. Ascher (2004). Scientific Information and Uncertainty: Challenges for the Use of Science in Policymaking. Science and Engineering Ethics 10 (3):437-455.
    Science can reinforce the healthy aspects of the politics of the policy process, to identify and further the public interest by discrediting policy options serving only special interests and helping to select among “science-confident” and “hedging” options. To do so, scientists must learn how to manage and communicate the degree of uncertainty in scientific understanding and prediction, lest uncertainty be manipulated to discredit science or to justify inaction. For natural resource and environmental policy, the institutional interests (...)
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  39.  13
    George Wu (1999). Anxiety and Decision Making with Delayed Resolution of Uncertainty. Theory and Decision 46 (2):159-199.
    In many real-world gambles, a non-trivial amount of time passes before the uncertainty is resolved but after a choice is made. An individual may have a preference between gambles with identical probability distributions over final outcomes if they differ in the timing of resolution of uncertainty. In this domain, utility consists not only of the consumption of outcomes, but also the psychological utility induced by an unresolved gamble. We term this utility anxiety. Since a reflective decision (...)
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  40.  3
    Brice Laurent (2015). Operations for a Problem of Existence: Dealing with the Ontological Uncertainty of Nano Substances. Foundations of Chemistry 17 (3):207-224.
    This paper discusses the operations meant to act on situations of ontological uncertainties for chemicals. Using examples related to substances developed as part of nanotechnology programs, it analyses technical and social instruments meant to define the existence of these substances, as « new » or « existing » chemicals. Carbon nanotubes developed by a French company offer an illustration of containment, while the legal disputes about nano silver in the U.S. display oppositions about whether or not these compounds are equivalent (...)
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  41.  12
    Steven J. Brams & D. Marc Kilgour (1998). Backward Induction Is Not Robust: The Parity Problem and the Uncertainty Problem. [REVIEW] Theory and Decision 45 (3):263-289.
    A cornerstone of game theory is backward induction, whereby players reason backward from the end of a game in extensive form to the beginning in order to determine what choices are rational at each stage of play. Truels, or three-person duels, are used to illustrate how the outcome can depend on (1) the evenness/oddness of the number of rounds (the parity problem) and (2) uncertainty about the endpoint of the game (the uncertainty problem). Since there is (...)
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  42.  6
    Franz Baader, Hans-Jürgen Bürckert, Bernhard Nebel, Werner Nutt & Gert Smolka (1993). On the Expressivity of Feature Logics with Negation, Functional Uncertainty, and Sort Equations. Journal of Logic, Language and Information 2 (1):1-18.
    Feature logics are the logical basis for so-called unification grammars studied in computational linguistics. We investigate the expressivity of feature terms with negation and the functional uncertainty construct needed for the description of long-distance dependencies and obtain the following results: satisfiability of feature terms is undecidable, sort equations can be internalized, consistency of sort equations is decidable if there is at least one atom, and consistency of sort equations is undecidable if there is no atom.
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  43.  2
    Jeff Davis & Daniel Werre (2008). A Longitudinal Study of the Effects of Uncertainty on Reproductive Behaviors. Human Nature 19 (4):426-452.
    Uncertainty exerts powerful influences on life history decisions. This has been demonstrated in experiments on nonhumans and in mathematical models. Studies of human populations are suggestive of the effects of uncertainty, but they rely on measures of environmental stress. In this paper, we derive a new measure of uncertainty, upsilon (υ), for use in non-experimental studies. We estimate its association with reproductive behaviors in a longitudinal panel sample of adolescents in the United States. Results (...)
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  44.  15
    John Quiggin (2001). Production Under Uncertainty and Choice Under Uncertainty in the Emergence of Generalized Expected Utility Theory. Theory and Decision 51 (2/4):125-144.
    This paper presents a personal view of the interaction between the analysis of choice under uncertainty and the analysis of production under uncertainty. Interest in the foundations of the theory of choice under uncertainty was stimulated by applications of expected utility theory such as the Sandmo model of production under uncertainty. This interest led to the development of generalized models including rank-dependent expected utility theory. In turn, the development of generalized expected (...)
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  45.  43
    Sven Ove Hansson (2009). Measuring Uncertainty. Studia Logica 93 (1):21 - 40.
    Two types of measures of probabilistic uncertainty are introduced and investigated. Dispersion measures report how diffused the agent’s second-order probability distribution is over the range of first-order probabilities. Robustness measures reflect the extent to which the agent’s assessment of the prior (objective) probability of an event is perturbed by information about whether or not the event actually took place. The properties of both types of measures are investigated. The most obvious type of robustness measure is shown to (...)
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  46.  39
    Alistair Isaac & Tomohiro Hoshi (2011). Synchronizing Diachronic Uncertainty. Journal of Logic, Language and Information 20 (2):137-159.
    Diachronic uncertainty, uncertainty about where an agent falls in time, poses interesting conceptual difficulties. Although the agent is uncertain about where she falls in time, this uncertainty can only obtain at a particular moment in time. We resolve this conceptual tension by providing a transformation from models with diachronic uncertainty relations into “equivalent” models with only synchronic uncertainty relations. The former are interpreted as capturing the causal structure of a situation, while the latter are interpreted (...)
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  47.  10
    Marko Ahteensuu & Susanna Lehvävirta (2014). Assisted Migration, Risks and Scientific Uncertainty, and Ethics: A Comment on Albrecht Et Al.'S Review Paper. Journal of Agricultural and Environmental Ethics 27 (3):471-477.
    In response to Albrecht et al.’s (J Agric Environ Ethics 26(4):827–845, 2013) discussion on the ethics of assisted migration, we emphasize the issues of risk and scientific uncertainty as an inextricable part of a comprehensive ethical evaluation. Insisting on a separation of risk and ethical considerations, although arguably common in many policy contexts, is at best misguided and at worst damaging.
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  48.  29
    Gert de Cooman & Peter Walley (2002). A Possibilistic Hierarchical Model for Behaviour Under Uncertainty. Theory and Decision 52 (4):327-374.
    Hierarchical models are commonly used for modelling uncertainty. They arise whenever there is a `correct' or `ideal' uncertainty model but the modeller is uncertain about what it is. Hierarchical models which involve probability distributions are widely used in Bayesian inference. Alternative models which involve possibility distributions have been proposed by several authors, but these models do not have a clear operational meaning. This paper describes a new hierarchical model which is mathematically equivalent to some of the (...)
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    Jonas Clausen Mork (2013). Uncertainty, Credal Sets and Second Order Probability. Synthese 190 (3):353-378.
    The last 20 years or so has seen an intense search carried out within Dempster–Shafer theory, with the aim of finding a generalization of the Shannon entropy for belief functions. In that time, there has also been much progress made in credal set theory—another generalization of the traditional Bayesian epistemic representation—albeit not in this particular area. In credal set theory, sets of probability functions are utilized to represent the epistemic state of rational agents instead of the single probability function of (...)
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  50.  2
    Alexey E. Rastegin (2015). Uncertainty Relations for General Canonically Conjugate Observables in Terms of Unified Entropies. Foundations of Physics 45 (8):923-942.
    We study uncertainty relations for a general class of canonically conjugate observables. It is known that such variables can be approached within a limiting procedure of the Pegg–Barnett type. We show that uncertainty relations for conjugate observables in terms of generalized entropies can be obtained on the base of genuine finite-dimensional consideration. Due to the Riesz theorem, there exists an inequality between norm-like functionals of two probability distributions in finite dimensions. Using a limiting procedure of the (...)
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