Results for 'strictly proper scoring rule'

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  1.  33
    Strictly Proper Scoring Rules.Juergen Landes - unknown
    Epistemic scoring rules are the en vogue tool for justifications of the probability norm and further norms of rational belief formation. They are different in kind and application from statistical scoring rules from which they arose. In the first part of the paper I argue that statistical scoring rules, properly understood, are in principle better suited to justify the probability norm than their epistemic brethren. Furthermore, I give a justification of the probability norm applying statistical scoring (...)
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  2.  25
    Characterization of Proper and Strictly Proper Scoring Rules for Quantiles.Mark J. Schervish, Joseph B. Kadane & Teddy Seidenfeld - unknown
    We give necessary and sufficient conditions for a scoring rule to be proper for a quantile if utility is linear, and the distribution is unrestricted. We also give results when the set of distributions is limited, for example, to distributions that have first moments.
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  3.  67
    Evaluating second-order probability judgments with strictly proper scoring rules.Kathleen M. Whitcomb & P. George Benson - 1996 - Theory and Decision 41 (2):165-178.
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  4. Proper scoring rules, dominated forecasts, and coherence.Teddy Seidenfeld - unknown
    De Finetti introduced the concept of coherent previsions and conditional previsions through a gambling argument and through a parallel argument based on a quadratic scoring rule. He shows that the two arguments lead to the same concept of coherence. When dealing with events only, there is a rich class of scoring rules which might be used in place of the quadratic scoring rule. We give conditions under which a general strictly proper scoring (...)
     
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  5.  42
    Proper scoring rules in epistemic decision theory.Maomei Wang - 2020 - Dissertation, Lingnan University
    Epistemic decision theory aims to defend a variety of epistemic norms in terms of their facilitation of epistemic ends. One of the most important components of EpDT is known as a scoring rule. This thesis addresses some problems about scoring rules in EpDT. I consider scoring rules both for precise credences and for imprecise credences. For scoring rules in the context of precise credences, I examine the rationale for requiring a scoring rule to (...)
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  6.  26
    Necessary and Sufficient Conditions for Domination Results for Proper Scoring Rules.Alexander R. Pruss - 2024 - Review of Symbolic Logic 17 (1):132-143.
    Scoring rules measure the deviation between a forecast, which assigns degrees of confidence to various events, and reality. Strictly proper scoring rules have the property that for any forecast, the mathematical expectation of the score of a forecast p by the lights of p is strictly better than the mathematical expectation of any other forecast q by the lights of p. Forecasts need not satisfy the axioms of the probability calculus, but Predd et al. [9] (...)
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  7.  66
    A Characterization for the Spherical Scoring Rule.Victor Richmond Jose - 2009 - Theory and Decision 66 (3):263-281.
    Strictly proper scoring rules have been studied widely in statistical decision theory and recently in experimental economics because of their ability to encourage assessors to honestly provide their true subjective probabilities. In this article, we study the spherical scoring rule by analytically examining some of its properties and providing some new geometric interpretations for this rule. Moreover, we state a theorem which provides an axiomatic characterization for the spherical scoring rule. The objective (...)
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  8. Epistemic Consequentialism, Veritism, and Scoring Rules.Marc-Kevin Daoust & Charles Côté-Bouchard - 2023 - Erkenntnis 88 (4):1741-1765.
    We argue that there is a tension between two monistic claims that are the core of recent work in epistemic consequentialism. The first is a form of monism about epistemic value, commonly known as veritism: accuracy is the sole final objective to be promoted in the epistemic domain. The other is a form of monism about a class of epistemic scoring rules: that is, strictly proper scoring rules are the only legitimate measures of inaccuracy. These two (...)
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  9.  14
    A scoring rule and global inaccuracy measure for contingent varying importance.Pavel Janda - 2023 - Philosophical Studies 180 (12):3323-3352.
    Levinstein recently presented a challenge to accuracy-first epistemology. He claims that there is no strictly proper, truth-directed, additive, and differentiable scoring rule that recognises the contingency of varying importance, i.e., the fact that an agent might value the inaccuracy of her credences differently at different possible worlds. In my response, I will argue that accuracy-first epistemology can capture the contingency of varying importance while maintaining its commitment to additivity, propriety, truth-directedness, and differentiability. I will construct a (...)
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  10. Probabilistic coherence and proper scoring rules.Joel Predd, Robert Seiringer, Elliott Lieb, Daniel Osherson, H. Vincent Poor & Sanjeev Kulkarni - 2009 - IEEE Transactions on Information Theory 55 (10):4786-4792.
    We provide self-contained proof of a theorem relating probabilistic coherence of forecasts to their non-domination by rival forecasts with respect to any proper scoring rule. The theorem recapitulates insights achieved by other investigators, and clarifi es the connection of coherence and proper scoring rules to Bregman divergence.
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  11. Scoring Imprecise Credences: A Mildly Immodest Proposal.Conor Mayo-Wilson & Gregory Wheeler - 2016 - Philosophy and Phenomenological Research 92 (1):55-78.
    Jim Joyce argues for two amendments to probabilism. The first is the doctrine that credences are rational, or not, in virtue of their accuracy or “closeness to the truth” (1998). The second is a shift from a numerically precise model of belief to an imprecise model represented by a set of probability functions (2010). We argue that both amendments cannot be satisfied simultaneously. To do so, we employ a (slightly-generalized) impossibility theorem of Seidenfeld, Schervish, and Kadane (2012), who show that (...)
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  12.  16
    The uniqueness of local proper scoring rules: the logarithmic family.Jingni Yang - 2020 - Theory and Decision 88 (2):315-322.
    Local proper scoring rules provide convenient tools for measuring subjective probabilities. Savage, 783–801, 1971) has shown that the only local proper scoring rule for more than two exclusive events is the logarithmic family. We generalize Savage by relaxing the properness and the domain, and provide simpler proof.
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  13. Coherence with Proper Scoring Rules.Mark Schervish, Teddy Seidenfeld & Mark Schervish Joseph - unknown
    • Coherence1 for previsions of random variables with generalized betting; • Coherence2 for probability forecasts of events with Brier score penalty; • Coherence3 probability forecasts of events with various proper scoring rules.
     
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  14.  26
    The Role of 'Dutch Books' and of 'Proper Scoring Rules'.Bruno De Finetti - 1981 - British Journal for the Philosophy of Science 32 (1):55 - 56.
  15. The role of 'dutch books' and of 'proper scoring rules'.Bruno de Finetti - 1981 - British Journal for the Philosophy of Science 32 (1):55-56.
  16. Mohammed Abdellaoui/Editorial Statement 1–2 Mohammed Abdellaoui and Peter P. Wakker/The likelihood Method for Decision Under Uncertainty 3–76 AAJ Marley and R. Duncan Luce/Independence Properties Vis--Vis Several Utility Representations 77–143. [REVIEW]Davide P. Cervone, William V. Gehrlein, William S. Zwicker, Which Scoring Rule Maximizes Condorcet, Marcello Basili, Alain Chateauneuf & Fulvio Fontini - 2005 - Theory and Decision 58:409-410.
     
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  17. A Pragmatist’s Guide to Epistemic Utility.Benjamin Anders Levinstein - 2017 - Philosophy of Science 84 (4):613-638.
    We use a theorem from M. J. Schervish to explore the relationship between accuracy and practical success. If an agent is pragmatically rational, she will quantify the expected loss of her credence with a strictly proper scoring rule. Which scoring rule is right for her will depend on the sorts of decisions she expects to face. We relate this pragmatic conception of inaccuracy to the purely epistemic one popular among epistemic utility theorists.
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  18.  56
    Which Scoring Rule Maximizes Condorcet Efficiency Under Iac?Davide P. Cervone, William V. Gehrlein & William S. Zwicker - 2005 - Theory and Decision 58 (2):145-185.
    Consider an election in which each of the n voters casts a vote consisting of a strict preference ranking of the three candidates A, B, and C. In the limit as n→∞, which scoring rule maximizes, under the assumption of Impartial Anonymous Culture (uniform probability distribution over profiles), the probability that the Condorcet candidate wins the election, given that a Condorcet candidate exists? We produce an analytic solution, which is not the Borda Count. Our result agrees with recent (...)
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  19. An Accuracy Based Approach to Higher Order Evidence.Miriam Schoenfield - 2018 - Philosophy and Phenomenological Research 96 (3):690-715.
    The aim of this paper is to apply the accuracy based approach to epistemology to the case of higher order evidence: evidence that bears on the rationality of one's beliefs. I proceed in two stages. First, I show that the accuracy based framework that is standardly used to motivate rational requirements supports steadfastness—a position according to which higher order evidence should have no impact on one's doxastic attitudes towards first order propositions. The argument for this will require a generalization of (...)
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  20.  35
    Accuracy, probabilism and Bayesian update in infinite domains.Alexander R. Pruss - 2022 - Synthese 200 (6):1-29.
    Scoring rules measure the accuracy or epistemic utility of a credence assignment. A significant literature uses plausible conditions on scoring rules on finite sample spaces to argue for both probabilism—the doctrine that credences ought to satisfy the axioms of probabilism—and for the optimality of Bayesian update as a response to evidence. I prove a number of formal results regarding scoring rules on infinite sample spaces that impact the extension of these arguments to infinite sample spaces. A common (...)
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  21.  49
    Forecasting with Imprecise Probabilities.Teddy Seidenfeld, Mark J. Schervish & Joseph B. Kadane - unknown
    We review de Finetti’s two coherence criteria for determinate probabilities: coherence1defined in terms of previsions for a set of events that are undominated by the status quo – previsions immune to a sure-loss – and coherence2 defined in terms of forecasts for events undominated in Brier score by a rival forecast. We propose a criterion of IP-coherence2 based on a generalization of Brier score for IP-forecasts that uses 1-sided, lower and upper, probability forecasts. However, whereas Brier score is a (...) proper scoring rule for eliciting determinate probabilities, we show that there is no real-valuedstrictly proper IP-score. Nonetheless, with respect to either of two decision rules – Γ-maximin or E-admissibility-+-Γ-maximin – we give a lexicographic strictly proper IP-scoring rule that is based on Brier score. (shrink)
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  22. Degrees of incoherence, Dutch bookability & guidance value.Jason Konek - 2022 - Philosophical Studies 180 (2):395-428.
    Why is it good to be less, rather than more incoherent? Julia Staffel, in her excellent book “Unsettled Thoughts,” answers this question by showing that if your credences are incoherent, then there is some way of nudging them toward coherence that is guaranteed to make them more accurate and reduce the extent to which they are Dutch-bookable. This seems to show that such a nudge toward coherence makes them better fit to play their key epistemic and practical roles: representing the (...)
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  23. Information and Inaccuracy.William Roche & Tomoji Shogenji - 2018 - British Journal for the Philosophy of Science 69 (2):577-604.
    This article proposes a new interpretation of mutual information. We examine three extant interpretations of MI by reduction in doubt, by reduction in uncertainty, and by divergence. We argue that the first two are inconsistent with the epistemic value of information assumed in many applications of MI: the greater is the amount of information we acquire, the better is our epistemic position, other things being equal. The third interpretation is consistent with EVI, but it is faced with the problem of (...)
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  24. Conditionalization, cogency, and cognitive value.Graham Oddie - 1997 - British Journal for the Philosophy of Science 48 (4):533-541.
    Why should a Bayesian bother performing an experiment, one the result of which might well upset his own favored credence function? The Ramsey-Good theorem provides a decision theoretic answer. Provided you base your decision on expected utility, and the the experiment is cost-free, performing the experiment and then choosing has at least as much expected utility as choosing without further ado. Furthermore, doing the experiment is strictly preferable just in case at least one possible outcome of the experiment could (...)
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  25. Generalized Immodesty Principles in Epistemic Utility Theory.Alejandro Pérez Carballo - 2023 - Ergo: An Open Access Journal of Philosophy 10 (31):874–907.
    Epistemic rationality is typically taken to be immodest at least in this sense: a rational epistemic state should always take itself to be doing at least as well, epistemically and by its own light, than any alternative epistemic state. If epistemic states are probability functions and their alternatives are other probability functions defined over the same collection of proposition, we can capture the relevant sense of immodesty by claiming that epistemic utility functions are (strictly) proper. In this paper (...)
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  26.  22
    Information and Inaccuracy.William Roche & Tomoji Shogenji - 2016 - British Journal for the Philosophy of Science:axw025.
    This paper proposes a new interpretation of mutual information (MI). We examine three extant interpretations of MI by reduction in doubt, by reduction in uncertainty, and by divergence. We argue that the first two are inconsistent with the epistemic value of information (EVI) assumed in many applications of MI: the greater is the amount of information we acquire, the better is our epistemic position, other things being equal. The third interpretation is consistent with EVI, but it is faced with the (...)
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  27.  71
    The appropriate role of dispute resolution in building trust online.Colin Rule & Larry Friedberg - 2005 - Artificial Intelligence and Law 13 (2):193-205.
    This article examines the relationship between online dispute resolution (ODR) and trust. We discuss what trust is, why trust is important, and how trust develops. Our claim is that efforts to implement online dispute resolution on a site or service in a manner that promotes trust need to consider ODR as just one tool in a broader toolbox of trust-building tools and techniques. These techniques are amongst others marketing, education, trust seals, and transparency. By evaluating ODR in its proper (...)
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  28. In Favor of Logarithmic Scoring.Randall G. McCutcheon - 2019 - Philosophy of Science 86 (2):286-303.
    Shuford, Albert and Massengill proved, a half century ago, that the logarithmic scoring rule is the only proper measure of inaccuracy determined by a differentiable function of probability assigned the actual cell of a scored partition. In spite of this, the log rule has gained less traction in applied disciplines and among formal epistemologists that one might expect. In this paper we show that the differentiability criterion in the Shuford et. al. result is unnecessary and use (...)
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  29. Strict finitism.Crispin Wright - 1982 - Synthese 51 (2):203 - 282.
    Dummett's objections to the coherence of the strict finitist philosophy of mathematics are thus, at the present time at least, ill-taken. We have so far no definitive treatment of Sorites paradoxes; so no conclusive ground for dismissing Dummett's response — the response of simply writing off a large class of familiar, confidently handled expressions as semantically incoherent. I believe that cannot be the right response, if only because it threatens to open an unacceptable gulf between the insight into his own (...)
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  30. Scoring Rules and Epistemic Compromise.Sarah Moss - 2011 - Mind 120 (480):1053-1069.
    It is commonly assumed that when we assign different credences to a proposition, a perfect compromise between our opinions simply ‘splits the difference’ between our credences. I introduce and defend an alternative account, namely that a perfect compromise maximizes the average of the expected epistemic values that we each assign to alternative credences in the disputed proposition. I compare the compromise strategy I introduce with the traditional strategy of compromising by splitting the difference, and I argue that my strategy is (...)
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  31.  97
    Reconsidering the Relationship among Voluntary Acts, Strict Liability, and Negligence in Criminal Law.Larry Alexander - 1990 - Social Philosophy and Policy 7 (2):84.
    This essay, as will become obvious, owes a huge debt to Mark Kelman, particularly to his article “Interpretative Construction in the Substantive Criminal Law.” That debt is one of both concept and content. There is rich irony in my aping Kelman's deconstructionist enterprise, for I do not share his enthusiasm for either the “insights” or the political agenda of the Critical Legal Studies movement. I do not believe that either the law in general or the criminal law in particular is (...)
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  32. IP Scoring Rules: Foundations and Applications.Jason Konek - 2019 - Proceedings of Machine Learning Research 103:256-264.
  33.  30
    Logical Revisionism: Logical Rules vs. Structural Rules.Fabrice Pataut - unknown
    As far as logic is concerned, the conclusion of Michael Dummett's manifestability argument is that intuitionistic logic, as first developed by Heyting, satisfies the semantic requirements of antirealism. The argument may be roughly sketched as follows: since we cannot manifest a grasp of possibly justification-transcendent truth conditions, we must countenance conditions which are such that, at least in principle and by the very nature of the case, we are able to recognize that they are satisfied whenever they are. Intuitionistic logic (...)
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  34. On the preference for more specific reference classes.Paul D. Thorn - 2017 - Synthese 194 (6):2025-2051.
    In attempting to form rational personal probabilities by direct inference, it is usually assumed that one should prefer frequency information concerning more specific reference classes. While the preceding assumption is intuitively plausible, little energy has been expended in explaining why it should be accepted. In the present article, I address this omission by showing that, among the principled policies that may be used in setting one’s personal probabilities, the policy of making direct inferences with a preference for frequency information for (...)
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  35.  75
    Scoring Rules, Condorcet Efficiency and Social Homogeneity.Dominique Lepelley, Patrick Pierron & Fabrice Valognes - 2000 - Theory and Decision 49 (2):175-196.
    In a three-candidate election, a scoring rule s (s in [0,1]) assigns 1, s, and 0 points (respectively) to each first, second and third place in the individual preference rankings. The Condorcet efficiency of a scoring rule is defined as the conditional probability that this rule selects the winner in accordance with Condorcet criteria (three Condorcet criteria are considered in the paper). We are interested in the following question: What rule s has the greatest (...)
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  36.  7
    Scoring Rules, Condorcet Efficiency and Social Homogeneity.D. Lepelley, P. Pierron & F. Valognes - 2000 - Theory and Decision 49 (2):175-196.
    In a three-candidate election, a scoring rule λ, λ∈[0,1], assigns 1,λ and 0 points (respectively) to each first, second and third place in the individual preference rankings. The Condorcet efficiency of a scoring rule is defined as the conditional probability that this rule selects the winner in accordance with Condorcet criteria (three Condorcet criteria are considered in the paper). We are interested in the following question: What rule λ has the greatest Condorcet efficiency? After (...)
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  37.  12
    Cognitive penetration and taste predicates: making an exception to the rule.David Bordonaba-Plou - 2021 - Filosofia Unisinos 22 (1):12-20.
    The relevance of cognitive penetration has been pointed out concerning three fields within philosophy: philosophy of science, philosophy of mind, and epistemology. This paper argues that this phenomenon is also relevant to the philosophy of language. First, I will defend that there are situations where ethical, social, or cultural rules can affect our taste perceptions. This influence can cause speakers to utter conflicting contents that lead them to disagree and, subsequently, to negotiate the circumstances of application of the taste predicates (...)
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  38.  27
    Scoring rules and social choice properties: some characterizations.Bonifacio Llamazares & Teresa Peña - 2015 - Theory and Decision 78 (3):429-450.
    In many voting systems, voters’ preferences on a set of candidates are represented by linear orderings. In this context, scoring rules are well-known procedures to aggregate the preferences of the voters. Under these rules, each candidate obtains a fixed number of points, sk\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$s_k$$\end{document}, each time he/she is ranked k\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$k$$\end{document}th by one voter and the candidates are ordered according to the total number (...)
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  39. Acceptance, Aggregation and Scoring Rules.Jake Chandler - 2013 - Erkenntnis 78 (1):201-217.
    As the ongoing literature on the paradoxes of the Lottery and the Preface reminds us, the nature of the relation between probability and rational acceptability remains far from settled. This article provides a novel perspective on the matter by exploiting a recently noted structural parallel with the problem of judgment aggregation. After offering a number of general desiderata on the relation between finite probability models and sets of accepted sentences in a Boolean sentential language, it is noted that a number (...)
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  40.  97
    Accuracy, Verisimilitude, and Scoring Rules.Jeffrey Dunn - 2019 - Australasian Journal of Philosophy 97 (1):151-166.
    ABSTRACTSuppose that beliefs come in degrees. How should we then measure the accuracy of these degrees of belief? Scoring rules are usually thought to be the mathematical tool appropriate for this job. But there are many scoring rules, which lead to different ordinal accuracy rankings. Recently, Fallis and Lewis [2016] have given an argument that, if sound, rules out many popular scoring rules, including the Brier score, as genuine measures of accuracy. I respond to this argument, in (...)
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  41.  16
    Scoring rules and probability testing.Pieter Koele, Robert De Boo & Paul Verschure - 1987 - Bulletin of the Psychonomic Society 25 (4):280-282.
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  42.  92
    Logarithmic Market Scoring Rules for Modular Combinatorial Information Aggregation.Robin Hanson - unknown
    In practice, scoring rules elicit good probability estimates from individuals, while betting markets elicit good consensus estimates from groups. Market scoring rules combine these features, eliciting estimates from individuals or groups, with groups costing no more than individuals. Regarding a bet on one event given another event, only logarithmic versions preserve the probability of the given event. Logarithmic versions also preserve the conditional probabilities of other events, and so preserve conditional independence relations. Given logarithmic rules that elicit relative (...)
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  43. Calibration, coherence, and scoring rules.Teddy Seidenfeld - 1985 - Philosophy of Science 52 (2):274-294.
    Can there be good reasons for judging one set of probabilistic assertions more reliable than a second? There are many candidates for measuring "goodness" of probabilistic forecasts. Here, I focus on one such aspirant: calibration. Calibration requires an alignment of announced probabilities and observed relative frequency, e.g., 50 percent of forecasts made with the announced probability of.5 occur, 70 percent of forecasts made with probability.7 occur, etc. To summarize the conclusions: (i) Surveys designed to display calibration curves, from which a (...)
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  44.  21
    A general scoring rule.Wulf Gaertner & Yongsheng Xu - unknown
    This paper studies a ranking rule of the following type axiomatically: each voter places k candidates into n categories with ranks from n to 1 attached to these categories, the candidate(s) with the highest aggregate score is (are) the winner(s). We show that it is characterized by a monotonicity condition and a multi-stage cancellation property.
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  45.  12
    Optimizing positional scoring rules for rank aggregation.Ioannis Caragiannis, Xenophon Chatzigeorgiou, George A. Krimpas & Alexandros A. Voudouris - 2019 - Artificial Intelligence 267 (C):58-77.
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  46.  33
    Logarithmic Market Scoring Rules for Modular Combinatorial Information Aggregation. Prentice-Hall - unknown
    In practice, scoring rules elicit good probability estimates from individuals, while betting markets elicit good consensus estimates from groups. Market scoring rules combine these features, eliciting estimates from individuals or groups, with groups costing no more than individuals. Regarding a bet on one event given another event, only logarithmic versions preserve the probability of the given event. Logarithmic versions also preserve the conditional probabilities of other events, and so preserve conditional independence relations. Given logarithmic rules that elicit relative (...)
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  47. Advice-giving and scoring-rule-based arguments for probabilism.Branden Fitelson & Lara Buchak - unknown
    Dutch Book Arguments. B is susceptibility to sure monetary loss (in a certain betting set-up), and F is the formal role played by non-Pr b’s in the DBT and the Converse DBT. Representation Theorem Arguments. B is having preferences that violate some of Savage’s axioms (and/or being unrepresentable as an expected utility maximizer), and F is the formal role played by non-Pr b’s in the RT.
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  48. Separability assumptions in scoring-rule-based arguments for probabilism.Branden Fitelson & Lara Buchak - unknown
    - In decision theory, an agent is deciding how to value a gamble that results in different outcomes in different states. Each outcome gets a utility value for the agent.
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  49.  88
    Attitudes Toward Epistemic Risk and the Value of Experiments.Don Fallis - 2007 - Studia Logica 86 (2):215-246.
    Several different Bayesian models of epistemic utilities (see, e. g., [37], [24], [40], [46]) have been used to explain why it is rational for scientists to perform experiments. In this paper, I argue that a model-suggested independently by Patrick Maher [40] and Graham Oddie [46]-that assigns epistemic utility to degrees of belief in hypotheses provides the most comprehensive explanation. This is because this proper scoring rule (PSR) model captures a wider range of scientifically acceptable attitudes toward epistemic (...)
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  50.  39
    Book Orders for Market Scoring Rules.Robin Hanson - unknown
    This explains how to smoothly integrate booked orders with a combinatorial market maker, all for the general case of bets on E[x|A] for arbitrary random variables x and sets A.
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