Results for 'Conditional Probability'

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  1. Conditional Probability and Defeat.Trenton Merricks - 2002 - In James Beilby (ed.), Naturalism Defeated? Essays on Plantinga's Evolutionary Argument Against Naturalism. Cornell University Press. pp. 165-175.
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  2. Conditional Probability From an Ontological Point of View.Rani Lill Anjum, Johan Arnt Myrstad & Stephen Mumford - manuscript
    This paper argues that the technical notion of conditional probability, as given by the ratio analysis, is unsuitable for dealing with our pretheoretical and intuitive understanding of both conditionality and probability. This is an ontological account of conditionals that include an irreducible dispositional connection between the antecedent and consequent conditions and where the conditional has to be treated as an indivisible whole rather than compositional. The relevant type of conditionality is found in some well-defined group of (...)
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  3. Popper’s Laws of the Excess of the Probability of the Conditional Over the Conditional Probability.Georg J. W. Dorn - 1992/93 - Conceptus: Zeitschrift Fur Philosophie 26:3–61.
    Karl Popper discovered in 1938 that the unconditional probability of a conditional of the form ‘If A, then B’ normally exceeds the conditional probability of B given A, provided that ‘If A, then B’ is taken to mean the same as ‘Not (A and not B)’. So it was clear (but presumably only to him at that time) that the conditional probability of B given A cannot be reduced to the unconditional probability of (...)
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  4.  87
    Triviality Results, Conditional Probability, and Restrictor Conditionals.Jonathan Vandenburgh - manuscript
    Conditional probability is often used to represent the probability of the conditional. However, triviality results suggest that the thesis that the probability of the conditional always equals conditional probability leads to untenable conclusions. In this paper, I offer an interpretation of this thesis in a possible worlds framework, arguing that the triviality results make assumptions at odds with the use of conditional probability. I argue that these assumptions come from a (...)
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  5. Conditional Degree of Belief and Bayesian Inference.Jan Sprenger - 2020 - Philosophy of Science 87 (2):319-335.
    Why are conditional degrees of belief in an observation E, given a statistical hypothesis H, aligned with the objective probabilities expressed by H? After showing that standard replies are not satisfactory, I develop a suppositional analysis of conditional degree of belief, transferring Ramsey’s classical proposal to statistical inference. The analysis saves the alignment, explains the role of chance-credence coordination, and rebuts the charge of arbitrary assessment of evidence in Bayesian inference. Finally, I explore the implications of this analysis (...)
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  6. You Can’T Always Get What You Want: Some Considerations Regarding Conditional Probabilities.Wayne C. Myrvold - 2015 - Erkenntnis 80 (3):573-603.
    The standard treatment of conditional probability leaves conditional probability undefined when the conditioning proposition has zero probability. Nonetheless, some find the option of extending the scope of conditional probability to include zero-probability conditions attractive or even compelling. This article reviews some of the pitfalls associated with this move, and concludes that, for the most part, probabilities conditional on zero-probability propositions are more trouble than they are worth.
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  7. Swahili Conditional Constructions in Embodied Frames of Reference: Modeling Semantics, Pragmatics, and Context-Sensitivity in UML Mental Spaces.Roderick Fish - 2020 - Dissertation, Trinity Western University
    Studies of several languages, including Swahili [swa], suggest that realis (actual, realizable) and irrealis (unlikely, counterfactual) meanings vary along a scale (e.g., 0.0–1.0). T-values (True, False) and P-values (probability) account for this pattern. However, logic cannot describe or explain (a) epistemic stances toward beliefs, (b) deontic and dynamic stances toward states-of-being and actions, and (c) context-sensitivity in conditional interpretations. (a)–(b) are deictic properties (positions, distance) of ‘embodied’ Frames of Reference (FoRs)—space-time loci in which agents perceive and from which (...)
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  8. Is There a Dutch Book Argument for Probability Kinematics?Brad Armendt - 1980 - Philosophy of Science 47 (4):583-588.
    Dutch Book arguments have been presented for static belief systems and for belief change by conditionalization. An argument is given here that a rule for belief change which under certain conditions violates probability kinematics will leave the agent open to a Dutch Book.
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  9. Counterfactual Probability.Ginger Schultheis - manuscript
    Stalnaker's Thesis about indicative conditionals is, roughly, that the probability one ought to assign to an indicative conditional equals the probability that one ought to assign to its consequent conditional on its antecedent. The thesis seems right. If you draw a card from a standard 52-card deck, how confident are you that the card is a diamond if it's a red card? To answer this, you calculate the proportion of red cards that are diamonds -- that (...)
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  10. The Logic of Conditional Belief.Benjamin Eva - 2020 - Philosophical Quarterly 70 (281):759-779.
    The logic of indicative conditionals remains the topic of deep and intractable philosophical disagreement. I show that two influential epistemic norms—the Lockean theory of belief and the Ramsey test for conditional belief—are jointly sufficient to ground a powerful new argument for a particular conception of the logic of indicative conditionals. Specifically, the argument demonstrates, contrary to the received historical narrative, that there is a real sense in which Stalnaker’s semantics for the indicative did succeed in capturing the logic of (...)
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  11.  60
    Learning as Hypothesis Testing: Learning Conditional and Probabilistic Information.Jonathan Vandenburgh - manuscript
    The history of science is often conceptualized through 'paradigm shifts,' where the accumulation of evidence leads to abrupt changes in scientific theories. Experimental evidence suggests that this kind of hypothesis revision occurs in more mundane circumstances, such as when children learn concepts and when adults engage in strategic behavior. In this paper, I argue that the model of hypothesis testing can explain how people learn certain complex, theory-laden propositions such as conditional sentences ('If A, then B') and probabilistic constraints (...)
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  12.  92
    Counterepistemic Indicative Conditionals and Probability.J. R. G. Williams - manuscript
    *This work is no longer under development* Two major themes in the literature on indicative conditionals are that the content of indicative conditionals typically depends on what is known;1 that conditionals are intimately related to conditional probabilities.2 In possible world semantics for counterfactual conditionals, a standard assumption is that conditionals whose antecedents are metaphysically impossible are vacuously true.3 This aspect has recently been brought to the fore, and defended by Tim Williamson, who uses it in to characterize alethic necessity (...)
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  13.  69
    A Puzzle About Inferential Strength and Probability.Alexander Hughes - manuscript
    Inductive logic would be the logic of arguments that are not valid, but nevertheless justify belief in something like the way in which valid arguments would. Maybe we could describe it as the logic of “almost valid” arguments. There is a sort of transitivity to valid arguments. Valid arguments can be chained together to form arguments and such arguments are themselves valid. One wants to distinguish the “almost valid” arguments by noting that chains of “almost valid” arguments are weaker than (...)
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  14.  79
    Semantic Information Measure with Two Types of Probability for Falsification and Confirmation.Lu Chenguang - manuscript
    Logical Probability (LP) is strictly distinguished from Statistical Probability (SP). To measure semantic information or confirm hypotheses, we need to use sampling distribution (conditional SP function) to test or confirm fuzzy truth function (conditional LP function). The Semantic Information Measure (SIM) proposed is compatible with Shannon’s information theory and Fisher’s likelihood method. It can ensure that the less the LP of a predicate is and the larger the true value of the proposition is, the more information (...)
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  15. Reliability and Future True Belief: Reply to Olsson and Jönsson.Christoph Jäger - 2011 - Theoria 77 (3):223-237.
    In “Process Reliabilism and the Value Problem” I argue that Erik Olsson and Alvin Goldman's conditional probability solution to the value problem in epistemology is unsuccessful and that it makes significant internalist concessions. In “Kinds of Learning and the Likelihood of Future True Beliefs” Olsson and Martin Jönsson try to show that my argument does “not in the end reduce the plausibility” of Olsson and Goldman's account. Here I argue that, while Olsson and Jönsson clarify and amend the (...)
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  16. A Puzzle About Knowing Conditionals.Daniel Rothschild & Levi Spectre - 2018 - Noûs 52 (2):473-478.
    We present a puzzle about knowledge, probability and conditionals. We show that in certain cases some basic and plausible principles governing our reasoning come into conflict. In particular, we show that there is a simple argument that a person may be in a position to know a conditional the consequent of which has a low probability conditional on its antecedent, contra Adams’ Thesis. We suggest that the puzzle motivates a very strong restriction on the inference of (...)
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  17. 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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  18. 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 (...)
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  19. Learning Not to Be Naïve: A Comment on the Exchange Between Perrine/Wykstra and Draper.Lara Buchak - 2014 - In Trent Dougherty & Justin McBrayer (eds.), Skeptical Theism: New Essays. Oxford University Press.
    Does postulating skeptical theism undermine the claim that evil strongly confirms atheism over theism? According to Perrine and Wykstra, it does undermine the claim, because evil is no more likely on atheism than on skeptical theism. According to Draper, it does not undermine the claim, because evil is much more likely on atheism than on theism in general. I show that the probability facts alone do not resolve their disagreement, which ultimately rests on which updating procedure – conditionalizing or (...)
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  20. Against the Ramsey Test.A. Morton - 2004 - Analysis 64 (4):294-299.
    I argue against the Ramsey test connecting indicative conditionals with conditional probability, by means of examples in which conditional probability is high but the conditional is intuitively implausible. At the end of the paper, I connect these issues to patterns of belief revision.
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  21. THE CAUSAL-PROCESS-CHANCE-BASED ANALYSIS OF CONTERFACTUALS.Igal Kvart - manuscript
    Abstract In this paper I consider an easier-to-read and improved to a certain extent version of the causal chance-based analysis of counterfactuals that I proposed and argued for in my A Theory of Counterfactuals. Sections 2, 3 and 4 form Part I: In it, I survey the analysis of the core counterfactuals (in which, very roughly, the antecedent is compatible with history prior to it). In section 2 I go through the three main aspects of this analysis, which are the (...)
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  22. What Is a Cognitive System?Robert D. Rupert - forthcoming - Cognitive Semantics 5.
    A theory of cognitive systems individuation is presented and defended. The approach has some affinity with Leonard Talmy's Overlapping Systems Model of Cognitive Organization, and the paper's first section explores aspects of Talmy's view that are shared by the view developed herein. According to the view on offer -- the conditional probability of co-contribution account (CPC) -- a cognitive system is a collection of mechanisms that contribute, in overlapping subsets, to a wide variety of forms of intelligent behavior. (...)
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  23. Solving a Paradox of Evidential Equivalence.Cian Dorr, John Hawthorne & Yoaav Isaacs - forthcoming - Mind:fzaa022.
    David Builes presents a paradox concerning how confident you should be that any given member of an infinite collection of fair coins landed heads, conditional on the information that they were all flipped and only finitely many of them landed heads. We argue that if you should have any conditional credence at all, it should be 1/2.
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  24. Probabilities of Conditionals.Bas van Fraassen - 1976 - In C. Hooker (ed.), Foundations of probability theory, statistical inference, and statistical theories of science.
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  25. Reasoning About Uncertain Conditionals.Niki Pfeifer - 2014 - Studia Logica 102 (4):849-866.
    There is a long tradition in formal epistemology and in the psychology of reasoning to investigate indicative conditionals. In psychology, the propositional calculus was taken for granted to be the normative standard of reference. Experimental tasks, evaluation of the participants’ responses and psychological model building, were inspired by the semantics of the material conditional. Recent empirical work on indicative conditionals focuses on uncertainty. Consequently, the normative standard of reference has changed. I argue why neither logic nor standard probability (...)
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  26. Betting on Conditionals.Guy Politzer, David P. Over & Jean Baratgin - 2010 - Thinking and Reasoning 16 (3):172-197.
    A study is reported testing two hypotheses about a close parallel relation between indicative conditionals, if A then B, and conditional bets, I bet you that if A then B. The first is that both the indicative conditional and the conditional bet are related to the conditional probability, P(B|A). The second is that de Finetti's three-valued truth table has psychological reality for both types of conditional – true, false, or void for indicative conditionals and (...)
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  27. 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 can (...)
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  28. Conditionals, Indeterminacy, and Triviality.Justin Khoo - 2013 - Philosophical Perspectives 27 (1):260-287.
    This paper discusses and relates two puzzles for indicative conditionals: a puzzle about indeterminacy and a puzzle about triviality. Both puzzles arise because of Ramsey's Observation, which states that the probability of a conditional is equal to the conditional probability of its consequent given its antecedent. The puzzle of indeterminacy is the problem of reconciling this fact about conditionals with the fact that they seem to lack truth values at worlds where their antecedents are false. The (...)
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  29.  37
    The Triviality Result is Not Counter-Intuitive.Matheus Silva - manuscript
    The Equation (TE) states that the probability of A → B is the probability of B given A (Jeffrey, 1964: 702–703). Lewis has shown that the acceptance of TE implies that the probability of A → B is the probability of B, which is implausible: the probability of a conditional cannot plausibly be the same as the probability of its consequent, e.g., the probability that the match will light given that is struck (...)
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  30. The Structure of Epistemic Probabilities.Nevin Climenhaga - 2020 - Philosophical Studies 177 (11):3213-3242.
    The epistemic probability of A given B is the degree to which B evidentially supports A, or makes A plausible. This paper is a first step in answering the question of what determines the values of epistemic probabilities. I break this question into two parts: the structural question and the substantive question. Just as an object’s weight is determined by its mass and gravitational acceleration, some probabilities are determined by other, more basic ones. The structural question asks what probabilities (...)
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  31. Upping the Stakes and the Preface Paradox.Jonny Blamey - 2013 - In Frank Zenker (ed.), Bayesian Argumentation. Springer. pp. 195-210.
    Abstract The Preface Paradox, first introduced by David Makinson (1961), presents a plausible scenario where an agent is evidentially certain of each of a set of propositions without being evidentially certain of the conjunction of the set of propositions. Given reasonable assumptions about the nature of evidential certainty, this appears to be a straightforward contradiction. We solve the paradox by appeal to stake size sensitivity, which is the claim that evidential probability is sensitive to stake size. The argument is (...)
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  32. Inductive Support.Georg J. W. Dorn - 1991 - In Gerhard Schurz & Georg J. W. Dorn (eds.), Advances in Scientific Philosophy. Essays in Honour of Paul Weingartner on the Occasion of the 60th Anniversary of his Birthday. Rodopi. pp. 345.
    I set up two axiomatic theories of inductive support within the framework of Kolmogorovian probability theory. I call these theories ‘Popperian theories of inductive support’ because I think that their specific axioms express the core meaning of the word ‘inductive support’ as used by Popper (and, presumably, by many others, including some inductivists). As is to be expected from Popperian theories of inductive support, the main theorem of each of them is an anti-induction theorem, the stronger one of them (...)
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  33. Giving Your Knowledge Half a Chance.Andrew Bacon - 2014 - Philosophical Studies (2):1-25.
    One thousand fair causally isolated coins will be independently flipped tomorrow morning and you know this fact. I argue that the probability, conditional on your knowledge, that any coin will land tails is almost 1 if that coin in fact lands tails, and almost 0 if it in fact lands heads. I also show that the coin flips are not probabilistically independent given your knowledge. These results are uncomfortable for those, like Timothy Williamson, who take these probabilities to (...)
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  34. What Should I Believe About What Would Have Been the Case?Franz Huber - 2015 - Journal of Philosophical Logic 44 (1):81-110.
    The question I am addressing in this paper is the following: how is it possible to empirically test, or confirm, counterfactuals? After motivating this question in Section 1, I will look at two approaches to counterfactuals, and at how counterfactuals can be empirically tested, or confirmed, if at all, on these accounts in Section 2. I will then digress into the philosophy of probability in Section 3. The reason for this digression is that I want to use the way (...)
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  35. New Foundations for Counterfactuals.Franz Huber - 2014 - Synthese 191 (10):2167-2193.
    Philosophers typically rely on intuitions when providing a semantics for counterfactual conditionals. However, intuitions regarding counterfactual conditionals are notoriously shaky. The aim of this paper is to provide a principled account of the semantics of counterfactual conditionals. This principled account is provided by what I dub the Royal Rule, a deterministic analogue of the Principal Principle relating chance and credence. The Royal Rule says that an ideal doxastic agent’s initial grade of disbelief in a proposition \(A\) , given that the (...)
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  36. A Utility Based Evaluation of Logico-Probabilistic Systems.Paul D. Thorn & Gerhard Schurz - 2014 - Studia Logica 102 (4):867-890.
    Systems of logico-probabilistic (LP) reasoning characterize inference from conditional assertions interpreted as expressing high conditional probabilities. In the present article, we investigate four prominent LP systems (namely, systems O, P, Z, and QC) by means of computer simulations. The results reported here extend our previous work in this area, and evaluate the four systems in terms of the expected utility of the dispositions to act that derive from the conclusions that the systems license. In addition to conforming to (...)
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  37. Cancellation, Negation, and Rejection.Niels Skovgaard-Olsen, Peter Collins, Karolina Krzyżanowska, Ulrike Hahn & Karl Christoph Klauer - 2019 - Cognitive Psychology 108:42-71.
    In this paper, new evidence is presented for the assumption that the reason-relation reading of indicative conditionals ('if A, then C') reflects a conventional implicature. In four experiments, it is investigated whether relevance effects found for the probability assessment of indicative conditionals (Skovgaard-Olsen, Singmann, and Klauer, 2016a) can be classified as being produced by a) a conversational implicature, b) a (probabilistic) presupposition failure, or c) a conventional implicature. After considering several alternative hypotheses and the accumulating evidence from other studies (...)
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  38. Time's Arrow in a Quantum Universe: On the Status of Statistical Mechanical Probabilities.Eddy Keming Chen - 2020 - In Valia Allori (ed.), Statistical Mechanics and Scientific Explanation: Determinism, Indeterminism and Laws of Nature. World Scientific. pp. 479–515.
    In a quantum universe with a strong arrow of time, it is standard to postulate that the initial wave function started in a particular macrostate---the special low-entropy macrostate selected by the Past Hypothesis. Moreover, there is an additional postulate about statistical mechanical probabilities according to which the initial wave function is a ''typical'' choice in the macrostate. Together, they support a probabilistic version of the Second Law of Thermodynamics: typical initial wave functions will increase in entropy. Hence, there are two (...)
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  39. "When Do I Get My Money" a Probabilistic Theory of Knowledge.Jonny Blamey - 2011 - Dissertation, KCL
    The value of knowledge can vary in that knowledge of important facts is more valuable than knowledge of trivialities. This variation in the value of knowledge is mirrored by a variation in evidential standards. Matters of greater importance require greater evidential support. But all knowledge, however trivial, needs to be evidentially certain. So on one hand we have a variable evidential standard that depends on the value of the knowledge, and on the other, we have the invariant standard of evidential (...)
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  40. General Dynamic Triviality Theorems.Jeffrey Sanford Russell & John Hawthorne - 2016 - Philosophical Review 125 (3):307-339.
    Famous results by David Lewis show that plausible-sounding constraints on the probabilities of conditionals or evaluative claims lead to unacceptable results, by standard probabilistic reasoning. Existing presentations of these results rely on stronger assumptions than they really need. When we strip these arguments down to a minimal core, we can see both how certain replies miss the mark, and also how to devise parallel arguments for other domains, including epistemic “might,” probability claims, claims about comparative value, and so on. (...)
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  41. 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 (...)
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  42. Another Approach to Consensus and Maximally Informed Opinions with Increasing Evidence.Rush T. Stewart & Michael Nielsen - 2018 - Philosophy of Science (2):236-254.
    Merging of opinions results underwrite Bayesian rejoinders to complaints about the subjective nature of personal probability. Such results establish that sufficiently similar priors achieve consensus in the long run when fed the same increasing stream of evidence. Initial subjectivity, the line goes, is of mere transient significance, giving way to intersubjective agreement eventually. Here, we establish a merging result for sets of probability measures that are updated by Jeffrey conditioning. This generalizes a number of different merging results in (...)
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  43. Abominable KK Failures.Kevin Dorst - 2019 - Mind 128 (512):1227-1259.
    KK is the thesis that if you can know p, you can know that you can know p. Though it’s unpopular, a flurry of considerations has recently emerged in its favour. Here we add fuel to the fire: standard resources allow us to show that any failure of KK will lead to the knowability and assertability of abominable indicative conditionals of the form ‘If I don’t know it, p’. Such conditionals are manifestly not assertable—a fact that KK defenders can easily (...)
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  44.  73
    Knowledge Embedded.Dirk Kindermann - forthcoming - Synthese.
    How should we account for the contextual variability of knowledge claims? Many philosophers favour an invariantist account on which such contextual variability is due entirely to pragmatic factors, leaving no interesting context-sensitivity in the semantic meaning of ‘know that.’ I reject this invariantist division of labor by arguing that pragmatic invariantists have no principled account of embedded occurrences of ‘S knows/doesn’t know that p’: Occurrences embedded within larger linguistic con- structions such as conditional sentences, attitude verbs, expressions of (...), comparatives, and many others, I argue, give rise to a threefold problem of embedded implicatures. (shrink)
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  45. There Is No Pure Empirical Reasoning.Michael Huemer - 2017 - Philosophy and Phenomenological Research 95 (3):592-613.
    The justificatory force of empirical reasoning always depends upon the existence of some synthetic, a priori justification. The reasoner must begin with justified, substantive constraints on both the prior probability of the conclusion and certain conditional probabilities; otherwise, all possible degrees of belief in the conclusion are left open given the premises. Such constraints cannot in general be empirically justified, on pain of infinite regress. Nor does subjective Bayesianism offer a way out for the empiricist. Despite often-cited convergence (...)
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  46. No One Can Serve Two Epistemic Masters.J. Gallow - 2018 - Philosophical Studies 175 (10):2389-2398.
    Consider two epistemic experts—for concreteness, let them be two weather forecasters. Suppose that you aren’t certain that they will issue identical forecasts, and you would like to proportion your degrees of belief to theirs in the following way: first, conditional on either’s forecast of rain being x, you’d like your own degree of belief in rain to be x. Secondly, conditional on them issuing different forecasts of rain, you’d like your own degree of belief in rain to be (...)
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  47.  63
    Logic and Gambling.Stephen Spielman - manuscript
    This paper outlines a formal recursive wager resolution calculus (WRC) that provides a novel conceptual framework for sentential logic via bridge rules that link wager resolution with truth values. When paired with a traditional truth-centric criterion of logical soundness WRC generates a sentential logic that is broadly truth-conditional but not truth-functional, supports the rules of proof employed in standard mathematics, and is immune to the most vexing features of their traditional implementation. WRC also supports a novel probabilistic criterion of (...)
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  48. An Introduction to Logical Entropy and its Relation to Shannon Entropy.David Ellerman - 2013 - International Journal of Semantic Computing 7 (2):121-145.
    The logical basis for information theory is the newly developed logic of partitions that is dual to the usual Boolean logic of subsets. The key concept is a "distinction" of a partition, an ordered pair of elements in distinct blocks of the partition. The logical concept of entropy based on partition logic is the normalized counting measure of the set of distinctions of a partition on a finite set--just as the usual logical notion of probability based on the Boolean (...)
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  49. Putting Inferentialism and the Suppositional Theory of Conditionals to the Test.Niels Skovgaard-Olsen - 2017 - Dissertation, University of Freiburg
    This dissertation is devoted to empirically contrasting the Suppositional Theory of conditionals, which holds that indicative conditionals serve the purpose of engaging in hypothetical thought, and Inferentialism, which holds that indicative conditionals express reason relations. Throughout a series of experiments, probabilistic and truth-conditional variants of Inferentialism are investigated using new stimulus materials, which manipulate previously overlooked relevance conditions. These studies are some of the first published studies to directly investigate the central claims of Inferentialism empirically. In contrast, the Suppositional (...)
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  50.  57
    Logical Entropy: Introduction to Classical and Quantum Logical Information Theory.David Ellerman - 2018 - Entropy 20 (9):679.
    Logical information theory is the quantitative version of the logic of partitions just as logical probability theory is the quantitative version of the dual Boolean logic of subsets. The resulting notion of information is about distinctions, differences and distinguishability and is formalized using the distinctions of a partition. All the definitions of simple, joint, conditional and mutual entropy of Shannon information theory are derived by a uniform transformation from the corresponding definitions at the logical level. The purpose of (...)
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