Results for 'probabilistic modelling'

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  1. Probabilistic Semantics for Epistemic Modals: Normality Assumptions, Conditional Epistemic Spaces, and the Strength of `Must' and `Might'.Guillermo Del Pinal - forthcoming - Linguistics and Philosophy:1-42.
    The epistemic modal auxiliaries 'must' and 'might' are vehicles for expressing the force with which a proposition follows from some body of evidence or information. Standard approaches model these operators using quantificational modal logic, but probabilistic approaches are becoming increasingly influential. According to a traditional view, 'must' is a maximally strong epistemic operator and 'might' is a bare possibility one. A competing account---popular amongst proponents of a probabilisitic turn---says that, given a body of evidence, 'must p' entails that Pr(p) (...)
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  2. Context Probabilism.Seth Yalcin - 2012 - In M. Aloni, Maria Aloni, Vadim Kimmelmann, Floris Roelofson, Galit W. Sassoon, Katrin Schulz & Matthijs Westera (eds.), Logic, Language, and Meaning: 18th Amsterdam Colloquium, Amsterdam, The Netherlands, December 19-21, 2011, Revised Selected Papers. Berlin: Springer. pp. 12-21.
    We investigate a basic probabilistic dynamic semantics for a fragment containing conditionals, probability operators, modals, and attitude verbs, with the aim of shedding light on the prospects for adding probabilistic structure to models of the conversational common ground.
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  3. Probabilistic Causation and the Explanatory Role of Natural Selection.Pablo Razeto-Barry & Ramiro Frick - 2011 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 42 (3):344-355.
    The explanatory role of natural selection is one of the long-term debates in evolutionary biology. Nevertheless, the consensus has been slippery because conceptual confusions and the absence of a unified, formal causal model that integrates different explanatory scopes of natural selection. In this study we attempt to examine two questions: (i) What can the theory of natural selection explain? and (ii) Is there a causal or explanatory model that integrates all natural selection explananda? For the first question, we argue that (...)
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  4.  96
    A Model of Causal and Probabilistic Reasoning in Frame Semantics.Vasil Penchev - 2020 - Semantics eJournal (Elsevier: SSRN) 2 (18):1-4.
    Quantum mechanics admits a “linguistic interpretation” if one equates preliminary any quantum state of some whether quantum entity or word, i.e. a wave function interpret-able as an element of the separable complex Hilbert space. All possible Feynman pathways can link to each other any two semantic units such as words or term in any theory. Then, the causal reasoning would correspond to the case of classical mechanics (a single trajectory, in which any next point is causally conditioned), and the (...) reasoning, to the case of quantum mechanics (many Feynman trajectories). Frame semantics turns out to be the natural counterpart of that linguistic interpretation of quantum mechanics. (shrink)
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  5. Calibrating Generative Models: The Probabilistic Chomsky-Schützenberger Hierarchy.Thomas Icard - 2020 - Journal of Mathematical Psychology 95.
    A probabilistic Chomsky–Schützenberger hierarchy of grammars is introduced and studied, with the aim of understanding the expressive power of generative models. We offer characterizations of the distributions definable at each level of the hierarchy, including probabilistic regular, context-free, (linear) indexed, context-sensitive, and unrestricted grammars, each corresponding to familiar probabilistic machine classes. Special attention is given to distributions on (unary notations for) positive integers. Unlike in the classical case where the "semi-linear" languages all collapse into the regular languages, (...)
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  6.  79
    Probabilistic Justification Logic.Joseph Lurie - 2018 - Philosophies 3 (1):2-0.
    Justification logics are constructive analogues of modal logics. They are often used as epistemic logics, particularly as models of evidentialist justification. However, in this role, justification logics are defective insofar as they represent justification with a necessity-like operator, whereas actual evidentialist justification is usually probabilistic. This paper first examines and rejects extant candidates for solving this problem: Milnikel’s Logic of Uncertain Justifications, Ghari’s Hájek–Pavelka-Style Justification Logics and a version of probabilistic justification logic developed by Kokkinis et al. It (...)
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  7. An Improved Probabilistic Account of Counterfactual Reasoning.Christopher G. Lucas & Charles Kemp - 2015 - Psychological Review 122 (4):700-734.
    When people want to identify the causes of an event, assign credit or blame, or learn from their mistakes, they often reflect on how things could have gone differently. In this kind of reasoning, one considers a counterfactual world in which some events are different from their real-world counterparts and considers what else would have changed. Researchers have recently proposed several probabilistic models that aim to capture how people do (or should) reason about counterfactuals. We present a new model (...)
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  8. Which Models of Scientific Explanation Are (In)Compatible with IBE?Yunus Prasetya - forthcoming - British Journal for the Philosophy of Science.
    In this article, I explore the compatibility of inference to the best explanation (IBE) with several influential models and accounts of scientific explanation. First, I explore the different conceptions of IBE and limit my discussion to two: the heuristic conception and the objective Bayesian conception. Next, I discuss five models of scientific explanation with regard to each model’s compatibility with IBE. I argue that Philip Kitcher’s unificationist account supports IBE; Peter Railton’s deductive-nomological-probabilistic model, Wesley Salmon’s statistical-relevance Model, and Bas (...)
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  9. A Proposed Probabilistic Extension of the Halpern and Pearl Definition of ‘Actual Cause’.Luke Fenton-Glynn - 2017 - British Journal for the Philosophy of Science 68 (4):1061-1164.
    In their article 'Causes and Explanations: A Structural-Model Approach. Part I: Causes', Joseph Halpern and Judea Pearl draw upon structural equation models to develop an attractive analysis of 'actual cause'. Their analysis is designed for the case of deterministic causation. I show that their account can be naturally extended to provide an elegant treatment of probabilistic causation.
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  10. Rational Understanding: Toward a Probabilistic Epistemology of Acceptability.Finnur Dellsén - 2019 - Synthese 198 (3):2475-2494.
    To understand something involves some sort of commitment to a set of propositions comprising an account of the understood phenomenon. Some take this commitment to be a species of belief; others, such as Elgin and I, take it to be a kind of cognitive policy. This paper takes a step back from debates about the nature of understanding and asks when this commitment involved in understanding is epistemically appropriate, or ‘acceptable’ in Elgin’s terminology. In particular, appealing to lessons from the (...)
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  11. Does Perceptual Consciousness Overflow Cognitive Access? The Challenge From Probabilistic, Hierarchical Processes.Steven Gross & Jonathan Flombaum - 2017 - Mind and Language 32 (3):358-391.
    Does perceptual consciousness require cognitive access? Ned Block argues that it does not. Central to his case are visual memory experiments that employ post-stimulus cueing—in particular, Sperling's classic partial report studies, change-detection work by Lamme and colleagues, and a recent paper by Bronfman and colleagues that exploits our perception of ‘gist’ properties. We argue contra Block that these experiments do not support his claim. Our reinterpretations differ from previous critics' in challenging as well a longstanding and common view of visual (...)
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  12.  79
    Probabilistic Actual Causation.Fenton-Glynn Luke - manuscript
    Actual causes - e.g. Suzy's being exposed to asbestos - often bring about their effects - e.g. Suzy's suffering mesothelioma - probabilistically. I use probabilistic causal models to tackle one of the thornier difficulties for traditional accounts of probabilistic actual causation: namely probabilistic preemption.
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  13. Believing Probabilistic Contents: On the Expressive Power and Coherence of Sets of Sets of Probabilities.Catrin Campbell-Moore & Jason Konek - 2019 - Analysis Reviews:anz076.
    Moss (2018) argues that rational agents are best thought of not as having degrees of belief in various propositions but as having beliefs in probabilistic contents, or probabilistic beliefs. Probabilistic contents are sets of probability functions. Probabilistic belief states, in turn, are modeled by sets of probabilistic contents, or sets of sets of probability functions. We argue that this Mossean framework is of considerable interest quite independently of its role in Moss’ account of probabilistic (...)
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  14. Probabilistic Causality and Multiple Causation.Paul Humphreys - 1980 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1980:25 - 37.
    It is argued in this paper that although much attention has been paid to causal chains and common causes within the literature on probabilistic causality, a primary virtue of that approach is its ability to deal with cases of multiple causation. In doing so some ways are indicated in which contemporary sine qua non analyses of causation are too narrow (and ways in which probabilistic causality is not) and an argument by Reichenbach designed to provide a basis for (...)
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  15. Entanglement and Thermodynamics in General Probabilistic Theories.Giulio Chiribella & Carlo Maria Scandolo - 2015 - New Journal of Physics 17:103027.
    Entanglement is one of the most striking features of quantum mechanics, and yet it is not specifically quantum. More specific to quantum mechanics is the connection between entanglement and thermodynamics, which leads to an identification between entropies and measures of pure state entanglement. Here we search for the roots of this connection, investigating the relation between entanglement and thermodynamics in the framework of general probabilistic theories. We first address the question whether an entangled state can be transformed into another (...)
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  16. Bayesian Models and Simulations in Cognitive Science.Giuseppe Boccignone & Roberto Cordeschi - 2007 - Workshop Models and Simulations 2, Tillburg, NL.
    Bayesian models can be related to cognitive processes in a variety of ways that can be usefully understood in terms of Marr's distinction among three levels of explanation: computational, algorithmic and implementation. In this note, we discuss how an integrated probabilistic account of the different levels of explanation in cognitive science is resulting, at least for the current research practice, in a sort of unpredicted epistemological shift with respect to Marr's original proposal.
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  17. Mathematical Models of Games of Chance: Epistemological Taxonomy and Potential in Problem-Gambling Research.Catalin Barboianu - 2015 - UNLV Gaming Research and Review Journal 19 (1):17-30.
    Games of chance are developed in their physical consumer-ready form on the basis of mathematical models, which stand as the premises of their existence and represent their physical processes. There is a prevalence of statistical and probabilistic models in the interest of all parties involved in the study of gambling – researchers, game producers and operators, and players – while functional models are of interest more to math-inclined players than problem-gambling researchers. In this paper I present a structural analysis (...)
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  18. Invited Commentary: Multilevel Analysis of Individual Heterogeneity-a Fundamental Critique of the Current Probabilistic Risk Factor Epidemiology. Http://Www.Ncbi.Nlm.Nih.Gov/Pubmed/24925064.Juan Merlo - 2014 - American Journal of Epidemiology 180 (2):213-214.
    In this issue of the Journal, Dundas et al. (Am J Epidemiol. 2014;180(2):197–207) apply a hitherto infrequent multilevel analytical approach: multiple membership multiple classification (MMMC) models. Specifically, by adopting a life-course approach, they use a multilevel regression with individuals cross-classified in different contexts (i.e., families, early schools, and neighborhoods) to investigate self-reported health and mental health in adulthood. They provide observational evidence suggesting the relevance of the early family environment for launching public health interventions in childhood in order to improve (...)
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  19. Bell's Theorem Versus Local Realism in a Quaternionic Model of Physical Space.Joy Christian - 2019 - IEEE Access 7:133388-133409.
    In the context of EPR-Bohm type experiments and spin detections confined to spacelike hypersurfaces, a local, deterministic and realistic model within a Friedmann-Robertson-Walker spacetime with a constant spatial curvature (S^3 ) is presented that describes simultaneous measurements of the spins of two fermions emerging in a singlet state from the decay of a spinless boson. Exact agreement with the probabilistic predictions of quantum theory is achieved in the model without data rejection, remote contextuality, superdeterminism or backward causation. A singularity-free (...)
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  20. Origin of Life as a Probabilistic Event in the Universe.Dimitri Marques Abramov & Carlos Alberto Mourão-Junior - manuscript
    By means of a probabilistic mathematical model, we bring into discussion the origin of life as a stochastic process. We consider only the chance of information emergence in the proteome and genome under the ideal thermodynamic and chemical conditions. For a more realistic model, we used, as a parameter, the information amount in N. equitans genome, the simplest known nowadays, as the equivalent to the first living cell that could have emerged in primitive Earth. We estimated the probability of (...)
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  21. Should Causal Models Always Be Markovian? The Case of Multi-Causal Forks in Medicine.Donald Gillies & Aidan Sudbury - 2013 - European Journal for Philosophy of Science 3 (3):275-308.
    The development of causal modelling since the 1950s has been accompanied by a number of controversies, the most striking of which concerns the Markov condition. Reichenbach's conjunctive forks did satisfy the Markov condition, while Salmon's interactive forks did not. Subsequently some experts in the field have argued that adequate causal models should always satisfy the Markov condition, while others have claimed that non-Markovian causal models are needed in some cases. This paper argues for the second position by considering the (...)
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  22.  26
    Bayesian Test of Significance for Conditional Independence: The Multinomial Model.Julio Michael Stern, Pablo de Morais Andrade & Carlos Alberto de Braganca Pereira - 2014 - Entropy 16:1376-1395.
    Conditional independence tests have received special attention lately in machine learning and computational intelligence related literature as an important indicator of the relationship among the variables used by their models. In the field of probabilistic graphical models, which includes Bayesian network models, conditional independence tests are especially important for the task of learning the probabilistic graphical model structure from data. In this paper, we propose the full Bayesian significance test for tests of conditional independence for discrete datasets. The (...)
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  23. Learning as Hypothesis Testing: Learning Conditional and Probabilistic Information.Jonathan Vandenburgh - manuscript
    Complex constraints like conditionals ('If A, then B') and probabilistic constraints ('The probability that A is p') pose problems for Bayesian theories of learning. Since these propositions do not express constraints on outcomes, agents cannot simply conditionalize on the new information. Furthermore, a natural extension of conditionalization, relative information minimization, leads to many counterintuitive predictions, evidenced by the sundowners problem and the Judy Benjamin problem. Building on the notion of a `paradigm shift' and empirical research in psychology and economics, (...)
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  24.  99
    Time Flow and Reversibility in a Probabilistic Universe.Andrew Thomas Holster - 1990 - Dissertation, Massey University
    A fundamental problem in understanding the nature of time is explaining its directionality. This 1990 PhD thesis re-examines the concepts of time flow, the physical directionality of time, and the semantics of tensed language. Several novel results are argued for that contradict the orthodox anti-realist views still dominant in the subject. Specifically, the concept of "metaphysical time flow" is supported as a valid scientific concept, and argued to be intrinsic to the directionality of objective probabilities in quantum mechanics; the common (...)
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  25. A Mathematical Model of Dignāga’s Hetu-Cakra.Aditya Kumar Jha - 2020 - Journal of Indian Council of Philosophical Research 37 (3):471-479.
    A reasoned argument or tarka is essential for a wholesome vāda that aims at establishing the truth. A strong tarka constitutes of a number of elements including an anumāna based on a valid hetu. Several scholars, such as Dharmakīrti, Vasubandhu and Dignāga, have worked on theories for the establishment of a valid hetu to distinguish it from an invalid one. This paper aims to interpret Dignāga’s hetu-cakra, called the wheel of grounds, from a modern philosophical perspective by deconstructing it into (...)
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  26. How Could a Rational Analysis Model Explain?Samuli Reijula - 2017 - COGSCI 2017: 39th Annual Conference of the Cognitive Science Society,.
    Rational analysis is an influential but contested account of how probabilistic modeling can be used to construct non-mechanistic but self-standing explanatory models of the mind. In this paper, I disentangle and assess several possible explanatory contributions which could be attributed to rational analysis. Although existing models suffer from evidential problems that question their explanatory power, I argue that rational analysis modeling can complement mechanistic theorizing by providing models of environmental affordances.
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  27.  49
    The Material Conditional is Sufficient to Model Deliberation.Giacomo Bonanno - forthcoming - Erkenntnis:1-25.
    There is an ongoing debate in the philosophical literature whether the conditionals that are central to deliberation are subjunctive or indicative conditionals and, if the latter, what semantics of the indicative conditional is compatible with the role that conditionals play in deliberation. We propose a possible-world semantics where conditionals of the form “if I take action a the outcome will be x” are interpreted as material conditionals. The proposed framework is illustrated with familiar examples and both qualitative and probabilistic (...)
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  28. Generalised Reichenbachian Common Cause Systems.Claudio Mazzola - 2019 - Synthese 196 (10):4185-4209.
    The principle of the common cause claims that if an improbable coincidence has occurred, there must exist a common cause. This is generally taken to mean that positive correlations between non-causally related events should disappear when conditioning on the action of some underlying common cause. The extended interpretation of the principle, by contrast, urges that common causes should be called for in order to explain positive deviations between the estimated correlation of two events and the expected value of their correlation. (...)
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  29.  19
    Rapid Initiative Assessment for Counter-IED Investment.Charles Twardy, Ed Wright, Tod Levitt, Kathryn Laskey & Kellen Leister - 2009 - In Proceedings of the Seventh Bayesian Applications Modeling Workshop.
    There is a need to rapidly assess the impact of new technology initiatives on the Counter Improvised Explosive Device battle in Iraq and Afghanistan. The immediate challenge is the need for rapid decisions, and a lack of engineering test data to support the assessment. The rapid assessment methodology exploits available information to build a probabilistic model that provides an explicit executable representation of the initiative’s likely impact. The model is used to provide a consistent, explicit, explanation to decision makers (...)
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  30. The Good, the Bad, and the Timely: How Temporal Order and Moral Judgment Influence Causal Selection.Kevin Reuter, Lara Kirfel, Raphael van Riel & Luca Barlassina - 2014 - Frontiers in Psychology 5 (1336):1-10.
    Causal selection is the cognitive process through which one or more elements in a complex causal structure are singled out as actual causes of a certain effect. In this paper, we report on an experiment in which we investigated the role of moral and temporal factors in causal selection. Our results are as follows. First, when presented with a temporal chain in which two human agents perform the same action one after the other, subjects tend to judge the later agent (...)
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  31. Coherence and Confirmation Through Causation.Gregory Wheeler & Richard Scheines - 2013 - Mind 122 (485):135-170.
    Coherentism maintains that coherent beliefs are more likely to be true than incoherent beliefs, and that coherent evidence provides more confirmation of a hypothesis when the evidence is made coherent by the explanation provided by that hypothesis. Although probabilistic models of credence ought to be well-suited to justifying such claims, negative results from Bayesian epistemology have suggested otherwise. In this essay we argue that the connection between coherence and confirmation should be understood as a relation mediated by the causal (...)
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  32. Causal Graphs and Biological Mechanisms.Alexander Gebharter & Marie I. Kaiser - 2014 - In Marie I. Kaiser, Oliver Scholz, Daniel Plenge & Andreas Hüttemann (eds.), Explanation in the special sciences: The case of biology and history. Dordrecht: Springer. pp. 55-86.
    Modeling mechanisms is central to the biological sciences – for purposes of explanation, prediction, extrapolation, and manipulation. A closer look at the philosophical literature reveals that mechanisms are predominantly modeled in a purely qualitative way. That is, mechanistic models are conceived of as representing how certain entities and activities are spatially and temporally organized so that they bring about the behavior of the mechanism in question. Although this adequately characterizes how mechanisms are represented in biology textbooks, contemporary biological research practice (...)
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  33. Impossible Worlds and Partial Belief.Edward Elliott - 2019 - Synthese 196 (8):3433-3458.
    One response to the problem of logical omniscience in standard possible worlds models of belief is to extend the space of worlds so as to include impossible worlds. It is natural to think that essentially the same strategy can be applied to probabilistic models of partial belief, for which parallel problems also arise. In this paper, I note a difficulty with the inclusion of impossible worlds into probabilistic models. Under weak assumptions about the space of worlds, most of (...)
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  34. Inference From Absence: The Case of Archaeology.Efraim Wallach - 2019 - Palgrave Communications 5 (94):1-10.
    Inferences from the absence of evidence to something are common in ordinary speech, but when used in scientific argumentations are usually considered deficient or outright false. Yet, as demonstrated here with the help of various examples, archaeologists frequently use inferences and reasoning from absence, often allowing it a status on par with inferences from tangible evidence. This discrepancy has not been examined so far. The article analyses it drawing on philosophical discussions concerning the validity of inference from absence, using (...) models that were originally developed to show that such inferences are weak and inconclusive. The analysis reveals that inference from absence can indeed be justified in many important situations of archaeological research, such as excavations carried out to explore the past existence and time-span of sedentary human habitation. The justification is closely related to the fact that archaeology explores the human past via its material remains. The same analysis points to instances where inference from absence can have comparable validity in other historical sciences, and to research questions in which archaeological inference from absence will be problematic or totally unwarranted. (shrink)
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  35. Destiny or Free Will Decision? A Life Overview From the Perspective of an Informational Modeling of Consciousness Part I: Information, Consciousness and Life Cycle.Florin Gaiseanu - 2019 - Gerontology and Geriatrics Studies 4 (3):1-6.
    We drive our lives permanently by decisions YES/NO, and even we no longer distinguish the elementary intermediary steps of such decisions most often, they form stereotyped chains that once triggered, they run unconsciously, daily facilitating our activities. We lead our lives actually by conscious decisions, each of such decisions establishing our future trajectory. The YES/NO dipole is actually the elemental evaluation and decisional unit in the informational transmission/reception equipment and lines and in computers, respectively. Based on a binary probabilistic (...)
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  36. Can We Close the Bohr-Einstein Quantum Debate.Marian Kupczynski - 2017 - Philosophical Transactions of the Royal Society A 375:20160392..
    Recent experiments allowed concluding that Bell-type inequalities are indeed violated thus it is important to understand what it means and how can we explain the existence of strong correlations between outcomes of distant measurements. Do we have to announce that: Einstein was wrong, Nature is nonlocal and nonlocal correlations are produced due to the quantum magic and emerge, somehow, from outside space-time? Fortunately such conclusions are unfounded because if supplementary parameters describing measuring instruments are correctly incorporated in a theoretical model (...)
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  37. Closing the Door on Quantum Nonlocality.Marian Kupczynski - 2018 - Entropy 363347 (363347):17.
    Bell-type inequalities are proven using oversimplified probabilistic models and/or counterfactual definiteness (CFD). If setting-dependent variables describing measuring instruments are correctly introduced, none of these inequalities may be proven. In spite of this, a belief in a mysterious quantum nonlocality is not fading. Computer simulations of Bell tests allow people to study the different ways in which the experimental data might have been created. They also allow for the generation of various counterfactual experiments’ outcomes, such as repeated or simultaneous measurements (...)
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  38. The New Tweety Puzzle: Arguments Against Monistic Bayesian Approaches in Epistemology and Cognitive Science.Matthias Unterhuber & Gerhard Schurz - 2013 - Synthese 190 (8):1407-1435.
    In this paper we discuss the new Tweety puzzle. The original Tweety puzzle was addressed by approaches in non-monotonic logic, which aim to adequately represent the Tweety case, namely that Tweety is a penguin and, thus, an exceptional bird, which cannot fly, although in general birds can fly. The new Tweety puzzle is intended as a challenge for probabilistic theories of epistemic states. In the first part of the paper we argue against monistic Bayesians, who assume that epistemic states (...)
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  39. The Epistemology of Disagreement: Why Not Bayesianism?Thomas Mulligan - forthcoming - Episteme.
    Disagreement is a ubiquitous feature of human life, and philosophers have dutifully attended to it. One important question related to disagreement is epistemological: How does a rational person change her beliefs (if at all) in light of disagreement from others? The typical methodology for answering this question is to endorse a steadfast or conciliatory disagreement norm (and not both) on a priori grounds and selected intuitive cases. In this paper, I argue that this methodology is misguided. Instead, a thoroughgoingly Bayesian (...)
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  40. Is the Quantum World Composed of Propensitons?Nicholas Maxwell - 2007 - In Mauricio Suarez (ed.), Probabilities, Causes and Propensities in Physics. Springer. pp. 221-243.
    In this paper I outline my propensiton version of quantum theory (PQT). PQT is a fully micro-realistic version of quantum theory that provides us with a very natural possible solution to the fundamental wave/particle problem, and is free of the severe defects of orthodox quantum theory (OQT) as a result. PQT makes sense of the quantum world. PQT recovers all the empirical success of OQT and is, furthermore, empirically testable (although not as yet tested). I argue that Einstein almost put (...)
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  41.  6
    Contextuality-by-Default Description of Bell Tests: Contextuality as the Rule and Not as an Exception.Marian Kupczynski - 2021 - Entropy 2021 (23):1104-1120.
    Contextuality and entanglement are valuable resources for quantum computing and quantum information. Bell inequalities are used to certify entanglement; thus, it is important to understand why and how they are violated. Quantum mechanics and behavioural sciences teach us that random variables ‘measuring’ the same content (the answer to the same Yes or No question) may vary, if ‘measured’ jointly with other random variables. Alice’s and Bob’s raw data confirm Einsteinian non-signaling, but setting dependent experimental protocols are used to create samples (...)
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  42.  22
    Independent Natural Extension for Choice Functions.Jason Konek, Arthur Van Camp & Kevin Blackwell - 2021 - PMLR 147:320-330.
    We investigate epistemic independence for choice functions in a multivariate setting. This work is a continuation of earlier work of one of the authors [23], and our results build on the characterization of choice functions in terms of sets of binary preferences recently established by De Bock and De Cooman [7]. We obtain the independent natural extension in this framework. Given the generality of choice functions, our expression for the independent natural extension is the most general one we are aware (...)
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  43.  12
    Cognitive Science: Recent Advances and Recurring Problems.Fred Adams, Joao Kogler & Osvaldo Pessoa Junior (eds.) - 2017 - Wilmington, DE, USA: Vernon Press.
    This book consists of an edited collection of original essays of the highest academic quality by seasoned experts in their fields of cognitive science. The essays are interdisciplinary, drawing from many of the fields known collectively as “the cognitive sciences.” Topics discussed represent a significant cross-section of the most current and interesting issues in cognitive science. Specific topics include matters regarding machine learning and cognitive architecture, the nature of cognitive content, the relationship of information to cognition, the role of language (...)
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  44.  80
    The Dispositional Account of Credence.Anna Mahtani - 2020 - Philosophical Studies 177 (3):727-745.
    In this paper I offer an alternative - the ‘dispositional account’ - to the standard account of imprecise probabilism. Whereas for the imprecise probabilist, an agent’s credal state is modelled by a set of credence functions, on the dispositional account an agent’s credal state is modelled by a set of sets of credence functions. On the face of it, the dispositional account looks less elegant than the standard account – so why should we be interested? I argue that the dispositional (...)
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  45. Demystifying Dilation.Arthur Paul Pedersen & Gregory Wheeler - 2014 - Erkenntnis 79 (6):1305-1342.
    Dilation occurs when an interval probability estimate of some event E is properly included in the interval probability estimate of E conditional on every event F of some partition, which means that one’s initial estimate of E becomes less precise no matter how an experiment turns out. Critics maintain that dilation is a pathological feature of imprecise probability models, while others have thought the problem is with Bayesian updating. However, two points are often overlooked: (1) knowing that E is stochastically (...)
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  46. Normality and Actual Causal Strength.Thomas Icard, Jonathan Kominsky & Joshua Knobe - 2017 - Cognition 161:80-93.
    Existing research suggests that people's judgments of actual causation can be influenced by the degree to which they regard certain events as normal. We develop an explanation for this phenomenon that draws on standard tools from the literature on graphical causal models and, in particular, on the idea of probabilistic sampling. Using these tools, we propose a new measure of actual causal strength. This measure accurately captures three effects of normality on causal judgment that have been observed in existing (...)
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  47. 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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  48. Stalnaker’s Thesis in Context.Andrew Bacon - 2015 - Review of Symbolic Logic 8 (1):131-163.
    In this paper I present a precise version of Stalnaker's thesis and show that it is both consistent and predicts our intuitive judgments about the probabilities of conditionals. The thesis states that someone whose total evidence is E should have the same credence in the proposition expressed by 'if A then B' in a context where E is salient as they have conditional credence in the proposition B expresses given the proposition A expresses in that context. The thesis is formalised (...)
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  49. Cultural Evolution in Vietnam’s Early 20th Century: A Bayesian Networks Analysis of Franco-Chinese House Designs.Quan-Hoang Vuong, Quang-Khiem Bui, Viet-Phuong La, Thu-Trang Vuong, Manh-Toan Ho, Hong-Kong T. Nguyen, Hong-Ngoc Nguyen, Kien-Cuong P. Nghiem & Manh-Tung Ho - manuscript
    The study of cultural evolution has taken on an increasingly interdisciplinary and diverse approach in explicating phenomena of cultural transmission and adoptions. Inspired by this computational movement, this study uses Bayesian networks analysis, combining both the frequentist and the Hamiltonian Markov chain Monte Carlo (MCMC) approach, to investigate the highly representative elements in the cultural evolution of a Vietnamese city’s architecture in the early 20th century. With a focus on the façade design of 68 old houses in Hanoi’s Old Quarter (...)
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  50. Deontic Modals and Probability: One Theory to Rule Them All?Fabrizio Cariani - forthcoming - In Nate Charlow & Matthew Chrisman (eds.), Deontic Modality. Oxford University Press.
    This paper motivates and develops a novel semantic framework for deontic modals. The framework is designed to shed light on two things: the relationship between deontic modals and substantive theories of practical rationality and the interaction of deontic modals with conditionals, epistemic modals and probability operators. I argue that, in order to model inferential connections between deontic modals and probability operators, we need more structure than is provided by classical intensional theories. In particular, we need probabilistic structure that interacts (...)
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