Results for 'Branden Fitelson Kenny Easwaran'

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  1.  16
    An ‘Evidentialist’ Worry About Joyce's Argument for Probabilism.Branden Fitelson Kenny Easwaran - 2012 - Dialectica 66 (3):425-433.
    Joyce () argues that for any credence function that doesn't satisfy the probability axioms, there is another function that dominates it in terms of accuracy. But if some potential credence functions are ruled out as violations of the Principal Principle, then some non‐probabilistic credence functions fail to be dominated. We argue that to fix Joyce's argument, one must show that all epistemic values for credence functions derive from accuracy.
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  2. Accuracy, Coherence and Evidence.Branden Fitelson & Kenny Easwaran - 2015 - Oxford Studies in Epistemology 5:61-96.
    Taking Joyce’s (1998; 2009) recent argument(s) for probabilism as our point of departure, we propose a new way of grounding formal, synchronic, epistemic coherence requirements for (opinionated) full belief. Our approach yields principled alternatives to deductive consistency, sheds new light on the preface and lottery paradoxes, and reveals novel conceptual connections between alethic and evidential epistemic norms.
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  3. An 'evidentialist' worry about Joyce's argument for Probabilism.Kenny Easwaran & Branden Fitelson - 2012 - Dialetica 66 (3):425-433.
    To the extent that we have reasons to avoid these “bad B -properties”, these arguments provide reasons not to have an incoherent credence function b — and perhaps even reasons to have a coherent one. But, note that these two traditional arguments for probabilism involve what might be called “pragmatic” reasons (not) to be (in)coherent. In the case of the Dutch Book argument, the “bad” property is pragmatically bad (to the extent that one values money). But, it is not clear (...)
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  4. Partial belief, full belief, and accuracy–dominance.Branden Fitelson & Kenny Easwaran - manuscript
    Arguments for probabilism aim to undergird/motivate a synchronic probabilistic coherence norm for partial beliefs. Standard arguments for probabilism are all of the form: An agent S has a non-probabilistic partial belief function b iff (⇐⇒) S has some “bad” property B (in virtue of the fact that their p.b.f. b has a certain kind of formal property F). These arguments rest on Theorems (⇒) and Converse Theorems (⇐): b is non-Pr ⇐⇒ b has formal property F.
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  5. Decision Theory without Representation Theorems.Kenny Easwaran - 2014 - Philosophers' Imprint 14.
    Naive versions of decision theory take probabilities and utilities as primitive and use expected value to give norms on rational decision. However, standard decision theory takes rational preference as primitive and uses it to construct probability and utility. This paper shows how to justify a version of the naive theory, by taking dominance as the most basic normatively required preference relation, and then extending it by various conditions under which agents should be indifferent between acts. The resulting theory can make (...)
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  6. Probability.Branden Fitelson, Alan Hajek & Ned Hall - 2005 - In Sahotra Sarkar & Jessica Pfeifer (eds.), The Philosophy of Science: An Encyclopedia. New York: Routledge.
    There are two central questions concerning probability. First, what are its formal features? That is a mathematical question, to which there is a standard, widely (though not universally) agreed upon answer. This answer is reviewed in the next section. Second, what sorts of things are probabilities---what, that is, is the subject matter of probability theory? This is a philosophical question, and while the mathematical theory of probability certainly bears on it, the answer must come from elsewhere. To see why, observe (...)
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  7. Interview with Kenny Easwaran.Kenny Easwaran & William D'Alessandro - 2021 - The Reasoner 15 (2):9-12.
    Bill D'Alessandro talks to Kenny Easwaran about fractal music, Zoom conferences, being a good referee, teaching in math and philosophy, the rationalist community and its relationship to academia, decision-theoretic pluralism, and the city of Manhattan, Kansas.
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  8. Logical Foundations of Evidential Support.Branden Fitelson - 2006 - Philosophy of Science 73 (5):500-512.
    Carnap's inductive logic (or confirmation) project is revisited from an "increase in firmness" (or probabilistic relevance) point of view. It is argued that Carnap's main desiderata can be satisfied in this setting, without the need for a theory of "logical probability." The emphasis here will be on explaining how Carnap's epistemological desiderata for inductive logic will need to be modified in this new setting. The key move is to abandon Carnap's goal of bridging confirmation and credence, in favor of bridging (...)
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  9. Updating on the Credences of Others: Disagreement, Agreement, and Synergy.Kenny Easwaran, Luke Fenton-Glynn, Christopher Hitchcock & Joel D. Velasco - 2016 - Philosophers' Imprint 16 (11):1-39.
    We introduce a family of rules for adjusting one's credences in response to learning the credences of others. These rules have a number of desirable features. 1. They yield the posterior credences that would result from updating by standard Bayesian conditionalization on one's peers' reported credences if one's likelihood function takes a particular simple form. 2. In the simplest form, they are symmetric among the agents in the group. 3. They map neatly onto the familiar Condorcet voting results. 4. They (...)
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  10. How Bayesian Confirmation Theory Handles the Paradox of the Ravens.Branden Fitelson & James Hawthorne - 2010 - In Ellery Eells & James Fetzer (eds.), The Place of Probability in Science. Springer. pp. 247--275.
    The Paradox of the Ravens (a.k.a,, The Paradox of Confirmation) is indeed an old chestnut. A great many things have been written and said about this paradox and its implications for the logic of evidential support. The first part of this paper will provide a brief survey of the early history of the paradox. This will include the original formulation of the paradox and the early responses of Hempel, Goodman, and Quine. The second part of the paper will describe attempts (...)
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  11.  34
    Overview of Finite Propositional Boolean Algebras I.Branden Fitelson - unknown
    of monadic or relational predicate calculus (Fa, Gb, Rab, Hcd, etc.). • The Boolean Algebra BL set-up by such a language will be such that: – BL will have 2 n states (corresponding to the state descriptions of L) – BL will contain 2 2n propositions, in total. ∗ This is because each proposition p in BL is equivalent to a disjunction of state descriptions. Thus, each subset of the set of..
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  12.  34
    Introduction.Branden Fitelson - 2007 - Studia Logica 86 (3):351-352.
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  13.  6
    Introduction.Branden Fitelson - 2007 - Studia Logica 86 (2):147-148.
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  14.  26
    The evolution of logic.Kenny Easwaran - 2011 - Bulletin of Symbolic Logic 17 (4):533-535.
  15. Dr. Truthlove or: How I Learned to Stop Worrying and Love Bayesian Probabilities.Kenny Easwaran - 2016 - Noûs 50 (4):816-853.
    Many philosophers have argued that "degree of belief" or "credence" is a more fundamental state grounding belief. Many other philosophers have been skeptical about the notion of "degree of belief", and take belief to be the only meaningful notion in the vicinity. This paper shows that one can take belief to be fundamental, and ground a notion of "degree of belief" in the patterns of belief, assuming that an agent has a collection of beliefs that isn't dominated by some other (...)
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  16. Two Approaches to Belief Revision.Ted Shear & Branden Fitelson - 2019 - Erkenntnis 84 (3):487-518.
    In this paper, we compare and contrast two methods for the revision of qualitative beliefs. The first method is generated by a simplistic diachronic Lockean thesis requiring coherence with the agent’s posterior credences after conditionalization. The second method is the orthodox AGM approach to belief revision. Our primary aim is to determine when the two methods may disagree in their recommendations and when they must agree. We establish a number of novel results about their relative behavior. Our most notable finding (...)
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  17. Regularity and Hyperreal Credences.Kenny Easwaran - 2014 - Philosophical Review 123 (1):1-41.
    Many philosophers have become worried about the use of standard real numbers for the probability function that represents an agent's credences. They point out that real numbers can't capture the distinction between certain extremely unlikely events and genuinely impossible ones—they are both represented by credence 0, which violates a principle known as “regularity.” Following Skyrms 1980 and Lewis 1980, they recommend that we should instead use a much richer set of numbers, called the “hyperreals.” This essay argues that this popular (...)
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  18. Conditional Probabilities.Kenny Easwaran - 2019 - In Richard Pettigrew & Jonathan Weisberg (eds.), The Open Handbook of Formal Epistemology. PhilPapers Foundation. pp. 131-198.
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  19. Expected Accuracy Supports Conditionalization—and Conglomerability and Reflection.Kenny Easwaran - 2013 - Philosophy of Science 80 (1):119-142.
    Expected accuracy arguments have been used by several authors (Leitgeb and Pettigrew, and Greaves and Wallace) to support the diachronic principle of conditionalization, in updates where there are only finitely many possible propositions to learn. I show that these arguments can be extended to infinite cases, giving an argument not just for conditionalization but also for principles known as ‘conglomerability’ and ‘reflection’. This shows that the expected accuracy approach is stronger than has been realized. I also argue that we should (...)
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  20. Bayesianism I: Introduction and Arguments in Favor.Kenny Easwaran - 2011 - Philosophy Compass 6 (5):312-320.
    Bayesianism is a collection of positions in several related fields, centered on the interpretation of probability as something like degree of belief, as contrasted with relative frequency, or objective chance. However, Bayesianism is far from a unified movement. Bayesians are divided about the nature of the probability functions they discuss; about the normative force of this probability function for ordinary and scientific reasoning and decision making; and about what relation (if any) holds between Bayesian and non-Bayesian concepts.
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  21.  86
    Knowledge, Scepticism, and Defeat: Themes from Klein.Rodrigo Borges, Branden Fitelson & Cherie Braden (eds.) - 2019 - Springer Verlag.
    This is a collection of new essays written in honor of the work of Peter D. Klein, who has had and continues to have a tremendous influence in the development of epistemology. The essays reflect the breadth and depth of Klein’s work by engaging directly with his views and with the views of his interlocutors.
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  22. Probability, confirmation, and the conjunction fallacy.Vincenzo Crupi, Branden Fitelson & Katya Tentori - 2007 - Thinking and Reasoning 14 (2):182 – 199.
    The conjunction fallacy has been a key topic in debates on the rationality of human reasoning and its limitations. Despite extensive inquiry, however, the attempt to provide a satisfactory account of the phenomenon has proved challenging. Here we elaborate the suggestion (first discussed by Sides, Osherson, Bonini, & Viale, 2002) that in standard conjunction problems the fallacious probability judgements observed experimentally are typically guided by sound assessments of _confirmation_ relations, meant in terms of contemporary Bayesian confirmation theory. Our main formal (...)
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  23. Bayesianism II: Applications and Criticisms.Kenny Easwaran - 2011 - Philosophy Compass 6 (5):321-332.
    In the first paper, I discussed the basic claims of Bayesianism (that degrees of belief are important, that they obey the axioms of probability theory, and that they are rationally updated by either standard or Jeffrey conditionalization) and the arguments that are often used to support them. In this paper, I will discuss some applications these ideas have had in confirmation theory, epistemol- ogy, and statistics, and criticisms of these applications.
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  24. Probabilistic proofs and transferability.Kenny Easwaran - 2009 - Philosophia Mathematica 17 (3):341-362.
    In a series of papers, Don Fallis points out that although mathematicians are generally unwilling to accept merely probabilistic proofs, they do accept proofs that are incomplete, long and complicated, or partly carried out by computers. He argues that there are no epistemic grounds on which probabilistic proofs can be rejected while these other proofs are accepted. I defend the practice by presenting a property I call ‘transferability’, which probabilistic proofs lack and acceptable proofs have. I also consider what this (...)
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  25. Models and Reality—A Review of Brian Skyrms’s Evolution of the Social Contract.Martin Barrett, Ellery Eells, Branden Fitelson, Elliott Sober & Brian Skyrms - 1999 - Philosophy and Phenomenological Research 59 (1):237.
    Human beings are peculiar. In laboratory experiments, they often cooperate in one-shot prisoners’ dilemmas, they frequently offer 1/2 and reject low offers in the ultimatum game, and they often bid 1/2 in the game of divide-the-cake All these behaviors are puzzling from the point of view of game theory. The first two are irrational, if utility is measured in a certain way.1 The last isn’t positively irrational, but it is no more rational than other possible actions, since there are infinitely (...)
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  26. Why Countable Additivity?Kenny Easwaran - 2013 - Thought: A Journal of Philosophy 2 (1):53-61.
    It is sometimes alleged that arguments that probability functions should be countably additive show too much, and that they motivate uncountable additivity as well. I show this is false by giving two naturally motivated arguments for countable additivity that do not motivate uncountable additivity.
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  27. Book Review: Luc Bovens and Stephan Hartmann "Bayesian Epistemology". [REVIEW]Branden Fitelson - 2005 - Mind 114 (454):394-400.
    Book Review of Luc Bovens and Stephan Hartmann *Bayesian Epistemology* by Branden Fitelson.
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  28. Too Odd (Not) to Be True? A Reply to Olsson.Luc Bovens, Branden Fitelson, Stephan Hartmann & Josh Snyder - 2002 - British Journal for the Philosophy of Science 53 (4):539-563.
    Corroborating Testimony, Probability and Surprise’, Erik J. Olsson ascribes to L. Jonathan Cohen the claims that if two witnesses provide us with the same information, then the less probable the information is, the more confident we may be that the information is true (C), and the stronger the information is corroborated (C*). We question whether Cohen intends anything like claims (C) and (C*). Furthermore, he discusses the concurrence of witness reports within a context of independent witnesses, whereas the witnesses in (...)
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  29. Four Approaches to Supposition.Benjamin Eva, Ted Shear & Branden Fitelson - 2022 - Ergo: An Open Access Journal of Philosophy 8 (26):58-98.
    Suppositions can be introduced in either the indicative or subjunctive mood. The introduction of either type of supposition initiates judgments that may be either qualitative, binary judgments about whether a given proposition is acceptable or quantitative, numerical ones about how acceptable it is. As such, accounts of qualitative/quantitative judgment under indicative/subjunctive supposition have been developed in the literature. We explore these four different types of theories by systematically explicating the relationships canonical representatives of each. Our representative qualitative accounts of indicative (...)
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  30. Symmetries and asymmetries in evidential support.Ellery Eells & Branden Fitelson - 2002 - Philosophical Studies 107 (2):129 - 142.
    Several forms of symmetry in degrees of evidential support areconsidered. Some of these symmetries are shown not to hold in general. This has implications for the adequacy of many measures of degree ofevidential support that have been proposed and defended in the philosophical literature.
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  31. Strong and weak expectations.Kenny Easwaran - 2008 - Mind 117 (467):633-641.
    Fine has shown that assigning any value to the Pasadena game is consistent with a certain standard set of axioms for decision theory. However, I suggest that it might be reasonable to believe that the value of an individual game is constrained by the long-run payout of repeated plays of the game. Although there is no value that repeated plays of the Pasadena game converges to in the standard strong sense, I show that there is a weaker sort of convergence (...)
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  32. Monty hall, doomsday and confirmation.Darren Bradley & Branden Fitelson - 2003 - Analysis 63 (1):23–31.
    We give an analysis of the Monty Hall problem purely in terms of confirmation, without making any lottery assumptions about priors. Along the way, we show the Monty Hall problem is structurally identical to the Doomsday Argument.
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  33. The plurality of bayesian measures of confirmation and the problem of measure sensitivity.Branden Fitelson - 1999 - Philosophy of Science 66 (3):378.
    Contemporary Bayesian confirmation theorists measure degree of (incremental) confirmation using a variety of non-equivalent relevance measures. As a result, a great many of the arguments surrounding quantitative Bayesian confirmation theory are implicitly sensitive to choice of measure of confirmation. Such arguments are enthymematic, since they tacitly presuppose that certain relevance measures should be used (for various purposes) rather than other relevance measures that have been proposed and defended in the philosophical literature. I present a survey of this pervasive class of (...)
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  34. Studies in Bayesian Confirmation Theory.Branden Fitelson - 2001 - Dissertation, University of Wisconsin, Madison
    According to Bayesian confirmation theory, evidence E (incrementally) confirms (or supports) a hypothesis H (roughly) just in case E and H are positively probabilistically correlated (under an appropriate probability function Pr). There are many logically equivalent ways of saying that E and H are correlated under Pr. Surprisingly, this leads to a plethora of non-equivalent quantitative measures of the degree to which E confirms H (under Pr). In fact, many non-equivalent Bayesian measures of the degree to which E confirms (or (...)
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  35. The Role of Axioms in Mathematics.Kenny Easwaran - 2008 - Erkenntnis 68 (3):381-391.
    To answer the question of whether mathematics needs new axioms, it seems necessary to say what role axioms actually play in mathematics. A first guess is that they are inherently obvious statements that are used to guarantee the truth of theorems proved from them. However, this may neither be possible nor necessary, and it doesn’t seem to fit the historical facts. Instead, I argue that the role of axioms is to systematize uncontroversial facts that mathematicians can accept from a wide (...)
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  36. Why Physics Uses Second Derivatives.Kenny Easwaran - 2014 - British Journal for the Philosophy of Science 65 (4):845-862.
    I defend a causal reductionist account of the nature of rates of change like velocity and acceleration. This account identifies velocity with the past derivative of position and acceleration with the future derivative of velocity. Unlike most reductionist accounts, it can preserve the role of velocity as a cause of future positions and acceleration as the effect of current forces. I show that this is possible only if all the fundamental laws are expressed by differential equations of the same order. (...)
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  37.  82
    The philosophical significance of Stein’s paradox.Olav Vassend, Elliott Sober & Branden Fitelson - 2017 - European Journal for Philosophy of Science 7 (3):411-433.
    Charles Stein discovered a paradox in 1955 that many statisticians think is of fundamental importance. Here we explore its philosophical implications. We outline the nature of Stein’s result and of subsequent work on shrinkage estimators; then we describe how these results are related to Bayesianism and to model selection criteria like AIC. We also discuss their bearing on scientific realism and instrumentalism. We argue that results concerning shrinkage estimators underwrite a surprising form of holistic pragmatism.
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  38. Measuring confirmation and evidence.Ellery Eells & Branden Fitelson - 2000 - Journal of Philosophy 97 (12):663-672.
  39.  94
    A New Garber-Style Solution to the Problem of Old Evidence.Stephan Hartmann & Branden Fitelson - 2015 - Philosophy of Science 82 (4):712-717.
    In this discussion note, we explain how to relax some of the standard assumptions made in Garber-style solutions to the Problem of Old Evidence. The result is a more general and explanatory Bayesian approach.
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  40. Symmetries and asymmetries in evidential support.Ellery Eells & Branden Fitelson - 2011 - In Antony Eagle (ed.), Philosophy of Probability: Contemporary Readings. Routledge.
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  41. Diachronic and Interpersonal Coherence.Kenny Easwaran & Reuben Stern - forthcoming - In Baron Reed & A. K. Flowerree (eds.), Towards an Expansive Epistemology: Norms, Action, and the Social Sphere. Routledge.
    Bayesians standardly claim that there is rational pressure for agents’ credences to cohere across time because they face bad (epistemic or practical) consequences if they fail to diachronically cohere. But as David Christensen has pointed out, groups of individual agents also face bad consequences if they fail to interpersonally cohere, and there is no general rational pressure for one agent's credences to cohere with another’s. So it seems that standard Bayesian arguments may prove too much. Here, we agree with Christensen (...)
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  42.  38
    Rebutting and undercutting in mathematics.Kenny Easwaran - 2015 - Philosophical Perspectives 29 (1):146-162.
    In my () I argued that a central component of mathematical practice is that published proofs must be “transferable” — that is, they must be such that the author's reasons for believing the conclusion are shared directly with the reader, rather than requiring the reader to essentially rely on testimony. The goal of this paper is to explain this requirement of transferability in terms of a more general norm on defeat in mathematical reasoning that I will call “convertibility”. I begin (...)
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  43. Bullshit activities.Kenny Easwaran - forthcoming - Analytic Philosophy.
    Frankfurt gave an account of “bullshit” as a statement made without regard to truth or falsity. Austin argued that a large amount of language consists of speech acts aimed at goals other than truth or falsity. We don't want our account of bullshit to include all performatives. I develop a modification of Frankfurt's account that makes interesting and useful categorizations of various speech acts as bullshit or not and show that this account generalizes to many other kinds of act as (...)
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  44. Formal Epistemology.Kenny Easwaran - 2015 - Journal of Philosophical Logic 44 (6):651-662.
    Doxastic TheoriesThe application of formal tools to questions related to epistemology is of course not at all new. However, there has been a surge of interest in the field now known as “formal epistemology” over the past decade, with two annual conference series and an annual summer school at Carnegie Mellon University, in addition to many one-off events devoted to the field. A glance at the programs of these series illustrates the wide-ranging set of topics that have been grouped under (...)
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  45.  6
    1. Preface Preface (pp. i-ii).Laura Ruetsche, Chris Smeenk, Branden Fitelson, Patrick Maher, Martin Thomson‐Jones, Bas C. van Fraassen, Steven French, Juha Saatsi, Stathis Psillos & Katherine Brading - 2006 - Philosophy of Science 73 (5):i-ii.
  46. A probabilistic theory of coherence.Branden Fitelson - 2003 - Analysis 63 (3):194–199.
    Let E be a set of n propositions E1, ..., En. We seek a probabilistic measure C(E) of the ‘degree of coherence’ of E. Intuitively, we want C to be a quantitative, probabilistic generalization of the (deductive) logical coherence of E. So, in particular, we require C to satisfy the following..
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  47. Strengthening the case for knowledge from falsehood.Branden Fitelson - 2010 - Analysis 70 (4):666-669.
  48. Varieties of Conditional Probability.Kenny Easwaran - 2011 - In Prasanta Bandyopadhyay & Malcolm Forster (eds.), Handbook of the Philosophy of Science, Vol. 7: Philosophy of Statistics. North Holland.
    I consider the notions of logical probability, degree of belief, and objective chance, and argue that a different formalism for conditional probability is appropriate for each.
     
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  49. A classification of Newcomb problems and decision theories.Kenny Easwaran - 2019 - Synthese 198 (Suppl 27):6415-6434.
    Newcomb-like problems are classified by the payoff table of their act-state pairs, and the causal structure that gives rise to the act-state correlation. Decision theories are classified by the one or more points of intervention whose causal role is taken to be relevant to rationality in various problems. Some decision theories suggest an inherent conflict between different notions of rationality that are all relevant. Some issues with causal modeling raise problems for decision theories in the contexts where Newcomb problems arise.
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  50. Evidence of evidence is not (necessarily) evidence.Branden Fitelson - 2012 - Analysis 72 (1):85-88.
    In this note, I consider various precisifications of the slogan ‘evidence of evidence is evidence’. I provide counter-examples to each of these precisifications (assuming an epistemic probabilistic relevance notion of ‘evidential support’).
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