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25Investigation of the use of intervention data in estimating parameters in a Bayesian network
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40While in principle probabilistic logics might be applied to solve a range of problems, in practice they are rarely applied at present. This is perhaps because they seem disparate, complicated, and computationally intractable. However, we shall argue in this programmatic paper that several approaches to probabilistic logic into a simple unifying framework: logically complex evidence can be used to associate probability intervals or probabilities with sentences.
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41Possible semantics for a common framework of probabilistic logicsIn V. N. Huynh (ed.), International Workshop on Interval Probabilistic Uncertainty and Non-Classical Logics, Springer. 2008.In V. N. Huynh (ed.): Interval / Probabilistic Uncertainty and Non-Classical Logics, Advances in Soft Computing Series, Springer 2008, pp. 268-279. This paper proposes a common framework for various probabilistic logics. It consists of a set of uncertain premises with probabilities attached to them. This raises the question of the strength of a conclusion, but without imposing a particular semantics, no general solution is possible. The paper discusses several possible semantics by looking at it…Read more
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2*Wetenschapsfilosofie* door Leon Horsten, Igor Douven en Erik Weber (review)Algemeen Nederlands Tijdschrift voor Wijsbegeerte 100 (1): 80-83. 2008.
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66Possible Semantics for a Common Framework of Probabilistic LogicsIn V. N. Huynh (ed.), International Workshop on Interval Probabilistic Uncertainty and Non-Classical Logics, Springer. 2008.Summary. This paper proposes a common framework for various probabilistic logics. It consists of a set of uncertain premises with probabilities attached to them. This raises the question of the strength of a conclusion, but without imposing a particular semantics, no general solution is possible. The paper discusses several possible semantics by looking at it from the perspective of probabilistic argumentation.
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29Logical relations in a statistical problemIn Benedikt Löwe, Eric Pacuit & Jan-Willem Romeijn (eds.), Foundations of the Formal Sciences Vi: Probabilistic Reasoning and Reasoning With Probabilities. Studies in Logic, College Publication. 2008.This paper presents the progicnet programme. It proposes a general framework for probabilistic logic that can guide inference based on both logical and probabilistic input. After an introduction to the framework as such, it is illustrated by means of a toy example from psychometrics. It is shown that the framework can accommodate a number of approaches to probabilistic reasoning: Bayesian statistical inference, evidential probability, probabilistic argumentation, and objective Bayesianism. The f…Read more
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84Radical Uncertainty: Beyond Probabilistic Models of BeliefErkenntnis 79 (6): 1221-1223. 2014.Over the past decades or so the probabilistic model of rational belief has enjoyed increasing interest from researchers in epistemology and the philosophy of science. Of course, such probabilistic models were used for much longer in economics, in game theory, and in other disciplines concerned with decision making. Moreover, Carnap and co-workers used probability theory to explicate philosophical notions of confirmation and induction, thereby targeting epistemic rather than decision-theoretic as…Read more
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16Individual and social deliberation: IntroductionEconomics and Philosophy 31 (1): 1-2. 2015.Deliberation is the process through which we decide what do to, or what to believe. When we think about what to do, we are engaged in practical deliberation. Theoretical deliberation is when we think about what to believe, or about which judgement to make.
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51All agreed: Aumann meets DeGrootTheory and Decision 85 (1): 41-60. 2018.We represent consensus formation processes based on iterated opinion pooling as a dynamic approach to common knowledge of posteriors :1236–1239, 1976; Geanakoplos and Polemarchakis in J Econ Theory 28:192–200, 1982). We thus provide a concrete and plausible Bayesian rationalization of consensus through iterated pooling. The link clarifies the conditions under which iterated pooling can be rationalized from a Bayesian perspective, and offers an understanding of iterated pooling in terms of higher…Read more
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EPSA 15 Selected Papers, European Studies in Philosophy of Science, Vol. 5 (edited book)Springer. 2017.This edited collection showcases some of the best recent research in the philosophy of science. It comprises of thematically arranged papers presented at the 5th conference of the European Philosophy of Science Association (EPSA15), covering a broad variety of topics within general philosophy of science, and philosophical issues pertaining to specific sciences. The collection will appeal to researchers with an interest in the philosophical underpinnings of their own discipline, and to philosophe…Read more
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Foundations of the Formal Sciences Vi: Probabilistic Reasoning and Reasoning With Probabilities. Studies in Logic (edited book)College Publication. 2008.
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115Probabilistic Logics and Probabilistic NetworksSynthese Library. 2010.Additionally, the text shows how to develop computationally feasible methods to mesh with this framework.
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291The discursive dilemma as a lottery paradoxEconomics and Philosophy 23 (3): 301-319. 2007.List and Pettit have stated an impossibility theorem about the aggregation of individual opinion states. Building on recent work on the lottery paradox, this paper offers a variation on that result. The present result places different constraints on the voting agenda and the domain of profiles, but it covers a larger class of voting rules, which need not satisfy the proposition-wise independence of votes
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114Probabilist antirealismPacific Philosophical Quarterly 91 (1): 38-63. 2010.Until now, antirealists have offered sketches of a theory of truth, at best. In this paper, we present a probabilist account of antirealist truth in some formal detail, and we assess its ability to deal with the problems that are standardly taken to beset antirealism.
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84Mechanistic curiosity will not kill the Bayesian catBehavioral and Brain Sciences 34 (4): 192-193. 2011.Jones & Love (J&L) suggest that Bayesian approaches to the explanation of human behavior should be constrained by mechanistic theories. We argue that their proposal misconstrues the relation between process models, such as the Bayesian model, and mechanisms. While mechanistic theories can answer specific issues that arise from the study of processes, one cannot expect them to provide constraints in general
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39Intervention and Identifiability in Latent Variable ModellingMinds and Machines 28 (2): 243-264. 2018.We consider the use of interventions for resolving a problem of unidentified statistical models. The leading examples are from latent variable modelling, an influential statistical tool in the social sciences. We first explain the problem of statistical identifiability and contrast it with the identifiability of causal models. We then draw a parallel between the latent variable models and Bayesian networks with hidden nodes. This allows us to clarify the use of interventions for dealing with uni…Read more
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27Good Listeners, Wise Crowds, and Parasitic ExpertsAnalyse & Kritik 34 (2): 399-408. 2012.This article comments on the article of Thorn and Schurz in this volume and focuses on, what we call, the problem of parasitic experts. We discuss that both meta- induction and crowd wisdom can be understood as pertaining to absolute reliability rather than comparative optimality, and we suggest that the involvement of reliability will provide a handle on this problem.
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171A new resolution of the Judy Benjamin ProblemMind 120 (479). 2011.A paper on how to adapt your probabilisitc beliefs when learning a conditional
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261Measurement invariance, selection invariance, and fair selection revisitedPsychological Methods 28 (3): 687-690. 2023.This note contains a corrective and a generalization of results by Borsboom et al. (2008), based on Heesen and Romeijn (2019). It highlights the relevance of insights from psychometrics beyond the context of psychological testing.
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74Theory Change and Bayesian Statistical InferencePhilosophy of Science 72 (5): 1174-1186. 2005.This paper addresses the problem that Bayesian statistical inference cannot accommodate theory change, and proposes a framework for dealing with such changes. It first presents a scheme for generating predictions from observations by means of hypotheses. An example shows how the hypotheses represent the theoretical structure underlying the scheme. This is followed by an example of a change of hypotheses. The paper then presents a general framework for hypotheses change, and proposes the minimiza…Read more
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13Wetenschapsfilosofie als grensgangerAlgemeen Nederlands Tijdschrift voor Wijsbegeerte 108 (4): 509-513. 2016.Amsterdam University Press is a leading publisher of academic books, journals and textbooks in the Humanities and Social Sciences. Our aim is to make current research available to scholars, students, innovators, and the general public. AUP stands for scholarly excellence, global presence, and engagement with the international academic community.
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88An Interpretation of Weights in Linear Opinion PoolingEpisteme 21 (1): 19-33. 2024.This paper explores the fact that linear opinion pooling can be represented as a Bayesian update on the opinions of others. It uses this fact to propose a new interpretation of the pooling weights. Relative to certain modelling assumptions the weights can be equated with the so-called truth-conduciveness known from the context of Condorcet's jury theorem. This suggests a novel way to elicit the weights.
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50Changing The Definition of The Kilogram: Insights For Psychiatric Disease ClassificationPhilosophy, Psychiatry, and Psychology 26 (4): 97-108. 2019.In psychiatry, many scientists desire to move from a classification system based on symptoms toward a system based on biological causes. The idea is that psychiatric diseases should be redefined such that each disease would be associated with specific biological causes. This desire is intelligible because causal disease models often facilitate understanding and identification of new ways to intervene in disease processes. In its attempt to move from syndromal to specific etiological definitions,…Read more
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330Epistemic Diversity and Editor Decisions: A Statistical Matthew EffectPhilosophers' Imprint 19. 2019.This paper offers a new angle on the common idea that the process of science does not support epistemic diversity. Under minimal assumptions on the nature of journal editing, we prove that editorial procedures, even when impartial in themselves, disadvantage less prominent research programs. This purely statistical bias in article selection further skews existing differences in the success rate and hence attractiveness of research programs, and exacerbates the reputation difference between the p…Read more
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36EPSA15 Selected Papers: The 5th conference of the European Philosophy of Science Association in Düsseldorf (edited book)Springer. 2017.This edited collection showcases some of the best recent research in the philosophy of science. It comprises of thematically arranged papers presented at the 5th conference of the European Philosophy of Science Association, covering a broad variety of topics within general philosophy of science, and philosophical issues pertaining to specific sciences. The collection will appeal to researchers with an interest in the philosophical underpinnings of their own discipline, and to philosophers who wi…Read more
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26What's in a model? Network models as tools instead of representations of what psychiatric disorders really areBehavioral and Brain Sciences 42. 2019.
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30Inherent Complexity: A Problem for Statistical Model EvaluationPhilosophy of Science 84 (5): 797-809. 2017.This article investigates a problem for statistical model evaluation, in particular for curve fitting: by employing a different family of curves we can fit any scatter plot almost perfectly at apparently minor cost in terms of model complexity. The problem is resolved by an appeal to prior probabilities. This leads to some general lessons about how to approach model evaluation.
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23Moving Beyond Traditional Null Hypothesis Testing: Evaluating Expectations DirectlyFrontiers in Psychology 2. 2011.