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  1. The Legitimate Route to the Scientific Truth - The Gondor Principle.Joseph Krecz - manuscript
    We leave in a beautiful and uniform world, a world where everything probable is possible. Since the epic theory of relativity many scientists have embarked in a pursuit of astonishing theoretical fantasies, abandoning the prudent and logical path to scientific inquiry. The theory is a complex theoretical framework that facilitates the understanding of the universal laws of physics. It is based on the space-time continuum fabric abstract concept, and it is well suited for interpreting cosmic events. However, it is not (...)
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  2. Justification, Normalcy and Evidential Probability.Martin Smith - manuscript
    NOTE: This paper is a reworking of some aspects of an earlier paper – ‘What else justification could be’ and also an early draft of chapter 2 of Between Probability and Certainty. I'm leaving it online as it has a couple of citations and there is some material here which didn't make it into the book (and which I may yet try to develop elsewhere). My concern in this paper is with a certain, pervasive picture of epistemic justification. On this (...)
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  3. Higher-Order Uncertainty.Kevin Dorst - forthcoming - In Mattias Skipper & Asbjørn Steglich Petersen (eds.), Higher-Order Evidence: New Essays.
    You have higher-order uncertainty iff you are uncertain of what opinions you should have. I defend three claims about it. First, the higher-order evidence debate can be helpfully reframed in terms of higher-order uncertainty. The central question becomes how your first- and higher-order opinions should relate—a precise question that can be embedded within a general, tractable framework. Second, this question is nontrivial. Rational higher-order uncertainty is pervasive, and lies at the foundations of the epistemology of disagreement. Third, the answer is (...)
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  4. Updating Without Evidence.Yoaav Isaacs & Jeffrey Sanford Russell - forthcoming - Noûs.
    Sometimes you are unreliable at fulfilling your doxastic plans: for example, if you plan to be fully confident in all truths, probably you will end up being fully confident in some falsehoods by mistake. In some cases, there is information that plays the classical role of *evidence*—your beliefs are perfectly discriminating with respect to some possible facts about the world—and there is a standard expected-accuracy-based justification for planning to *conditionalize* on this evidence. This planning-oriented justification extends to some cases where (...)
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  5. Tough Enough? Robust Satisficing as a Decision Norm for Long-Term Policy Analysis.Andreas L. Mogensen & David Thorstad - 2022 - Synthese 200 (1):1-26.
    This paper aims to open a dialogue between philosophers working in decision theory and operations researchers and engineers working on decision-making under deep uncertainty. Specifically, we assess the recommendation to follow a norm of robust satisficing when making decisions under deep uncertainty in the context of decision analyses that rely on the tools of Robust Decision-Making developed by Robert Lempert and colleagues at RAND. We discuss two challenges for robust satisficing: whether the norm might derive its plausibility from an implicit (...)
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  6. Deference Done Better.Kevin Dorst, Benjamin A. Levinstein, Bernhard Salow, Brooke E. Husic & Branden Fitelson - 2021 - Wiley: Philosophical Perspectives 35 (1):99-150.
    There are many things—call them ‘experts’—that you should defer to in forming your opinions. The trouble is, many experts are modest: they’re less than certain that they are worthy of deference. When this happens, the standard theories of deference break down: the most popular (“Reflection”-style) principles collapse to inconsistency, while their most popular (“New-Reflection”-style) variants allow you to defer to someone while regarding them as an anti-expert. We propose a middle way: deferring to someone involves preferring to make any decision (...)
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  7. Against Legal Probabilism.Martin Smith - 2021 - In Jon Robson & Zachary Hoskins (eds.), The Social Epistemology of Legal Trials. Routledge.
    Is it right to convict a person of a crime on the basis of purely statistical evidence? Many who have considered this question agree that it is not, posing a direct challenge to legal probabilism – the claim that the criminal standard of proof should be understood in terms of a high probability threshold. Some defenders of legal probabilism have, however, held their ground: Schoeman (1987) argues that there are no clear epistemic or moral problems with convictions based on purely (...)
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  8. Civil Liability and the 50%+ Standard of Proof.Martin Smith - 2021 - International Journal of Evidence and Proof 25 (3):183-199.
    The standard of proof applied in civil trials is the preponderance of evidence, often said to be met when a proposition is shown to be more than 50% likely to be true. A number of theorists have argued that this 50%+ standard is too weak – there are circumstances in which a court should find that the defendant is not liable, even though the evidence presented makes it more than 50% likely that the plaintiff’s claim is true. In this paper, (...)
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  9. Evidence: A Guide for the Uncertain.Kevin Dorst - 2020 - Philosophy and Phenomenological Research 100 (3):586-632.
    Assume that it is your evidence that determines what opinions you should have. I argue that since you should take peer disagreement seriously, evidence must have two features. (1) It must sometimes warrant being modest: uncertain what your evidence warrants, and (thus) uncertain whether you’re rational. (2) But it must always warrant being guided: disposed to treat your evidence as a guide. Surprisingly, it is very difficult to vindicate both (1) and (2). But diagnosing why this is so leads to (...)
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  10. Structuring Decisions Under Deep Uncertainty.Casey Helgeson - 2020 - Topoi 39 (2):257-269.
    Innovative research on decision making under ‘deep uncertainty’ is underway in applied fields such as engineering and operational research, largely outside the view of normative theorists grounded in decision theory. Applied methods and tools for decision support under deep uncertainty go beyond standard decision theory in the attention that they give to the structuring of decisions. Decision structuring is an important part of a broader philosophy of managing uncertainty in decision making, and normative decision theorists can both learn from, and (...)
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  11. Bayesian Decision Theory and Stochastic Independence.Philippe Mongin - 2020 - Philosophy of Science 87 (1):152-178.
    As stochastic independence is essential to the mathematical development of probability theory, it seems that any foundational work on probability should be able to account for this property. Bayesian decision theory appears to be wanting in this respect. Savage’s postulates on preferences under uncertainty entail a subjective expected utility representation, and this asserts only the existence and uniqueness of a subjective probability measure, regardless of its properties. What is missing is a preference condition corresponding to stochastic independence. To fill this (...)
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  12. Inductive Logic From the Viewpoint of Quantum Information.Vasil Penchev - 2020 - Logic and Philosophy of Mathematics eJournal (Elsevier: SSRN) 12 (13):1-2.
    The resolving of the main problem of quantum mechanics about how a quantum leap and a smooth motion can be uniformly described resolves also the problem of how a distribution of reliable data and a sequence of deductive conclusions can be uniformly described by means of a relevant wave function “Ψdata”.
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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 knowledge or her semantics for epistemic (...)
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  14. Subjective Probability as Sampling Propensity.Thomas Icard - 2016 - Review of Philosophy and Psychology 7 (4):863-903.
    Subjective probability plays an increasingly important role in many fields concerned with human cognition and behavior. Yet there have been significant criticisms of the idea that probabilities could actually be represented in the mind. This paper presents and elaborates a view of subjective probability as a kind of sampling propensity associated with internally represented generative models. The resulting view answers to some of the most well known criticisms of subjective probability, and is also supported by empirical work in neuroscience and (...)
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  15. Between Probability and Certainty: What Justifies Belief.Martin Smith - 2016 - Oxford University Press UK.
    This book explores a question central to philosophy--namely, what does it take for a belief to be justified or rational? According to a widespread view, whether one has justification for believing a proposition is determined by how probable that proposition is, given one's evidence. In this book this view is rejected and replaced with another: in order for one to have justification for believing a proposition, one's evidence must normically support it--roughly, one's evidence must make the falsity of that proposition (...)
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  16. Can It Be Rational to Have Faith?Lara Buchak - 2012 - In Jake Chandler & Victoria Harrison (eds.), Probability in the Philosophy of Religion. Oxford University Press. pp. 225.
    This paper provides an account of what it is to have faith in a proposition p, in both religious and mundane contexts. It is argued that faith in p doesn’t require adopting a degree of belief that isn’t supported by one’s evidence but rather it requires terminating one’s search for further evidence and acting on the supposition that p. It is then shown, by responding to a formal result due to I.J. Good, that doing so can be rational in a (...)
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  17. Carnap’s Thought on Inductive Logic.Yusuke Kaneko - 2012 - Philosophy Study 2 (11).
    Although we often see references to Carnap’s inductive logic even in modern literatures, seemingly its confusing style has long obstructed its correct understanding. So instead of Carnap, in this paper, I devote myself to its necessary and sufficient commentary. In the beginning part (Sections 2-5), I explain why Carnap began the study of inductive logic and how he related it with our thought on probability (Sections 2-4). Therein, I trace Carnap’s thought back to Wittgenstein’s Tractatus as well (Section 5). In (...)
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  18. The Confirmation of Singular Causal Statements by Carnap’s Inductive Logic.Yusuke Kaneko - 2012 - Logica Year Book 2011.
    The aim of this paper is to apply inductive logic to the field that, presumably, Carnap never expected: legal causation. Legal causation is expressible in the form of singular causal statements; but it is distinguished from the customary concept of scientific causation, because it is subjective. We try to express this subjectivity within the system of inductive logic. Further, by semantic complement, we compensate a defect found in our application, to be concrete, the impossibility of two-place predicates (for causal relationship) (...)
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  19. On the Martingale Representation Theorem and on Approximate Hedging a Contingent Claim in the Minimum Deviation Square Criterion.Nguyen Van Huu & Quan-Hoang Vuong - 2007 - In Ta-Tsien Li Rolf Jeltsch (ed.), Some Topics in Industrial and Applied Mathematics. Shanghai, China: World Scientific. pp. 134-151.
    In this work we consider the problem of the approximate hedging of a contingent claim in the minimum mean square deviation criterion. A theorem on martingale representation in case of discrete time and an application of the result for semi-continuous market model are also given.
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  20. Ranking Functions and Rankings on Languages.Franz Huber - 2006 - Artificial Intelligence 170 (4-5):462-471.
    The Spohnian paradigm of ranking functions is in many respects like an order-of-magnitude reverse of subjective probability theory. Unlike probabilities, however, ranking functions are only indirectly—via a pointwise ranking function on the underlying set of possibilities W —defined on a field of propositions A over W. This research note shows under which conditions ranking functions on a field of propositions A over W and rankings on a language L are induced by pointwise ranking functions on W and the set of (...)
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  21. From Classical to Intuitionistic Probability.Brian Weatherson - 2003 - Notre Dame Journal of Formal Logic 44 (2):111-123.
    We generalize the Kolmogorov axioms for probability calculus to obtain conditions defining, for any given logic, a class of probability functions relative to that logic, coinciding with the standard probability functions in the special case of classical logic but allowing consideration of other classes of "essentially Kolmogorovian" probability functions relative to other logics. We take a broad view of the Bayesian approach as dictating inter alia that from the perspective of a given logic, rational degrees of belief are those representable (...)
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