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Artigos de revistas sobre o assunto "Skeptical inference"
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Walker, Mark. "Occam’s Razor, Dogmatism, Skepticism, and Skeptical Dogmatism". International Journal for the Study of Skepticism 6, n.º 1 (15 de março de 2016): 1–29. http://dx.doi.org/10.1163/22105700-05011168.
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Underdetermination arguments for skepticism maintain that our common sense view of the external world is no better, evidentially speaking, than some skeptical competitors. An important and well-known response by dogmatists, those who believe our commonsense view is justified, appeals to abduction or inference to the best explanation. The predominant version of this strategy, going back at least to Locke, invokes Occam’s razor: dogmatists claim the common sense view is simpler than any of its skeptical alternatives and so has more to recommend it, evidentially speaking. This dispute has overshadowed another possible view: skeptical dogmatism. Skeptical dogmatists hold that we are justified in believing that the common sense view is probably false. I argue that skeptical dogmatism presents some interesting complications to the dialectic between the dogmatist and the skeptic. On the one hand, even if the dogmatist’s use of Occam’s razor is sufficient to rebut skepticism, in itself it is not sufficient to refute skeptical dogmatism. On the other hand, skeptics themselves, ironically, must, given the assumptions of the paper, appeal to something like Occam’s razor in order to avoid capitulating to skeptical dogmatism.
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HENDRICKS, PERRY. "Skeptical Theism Proved". Journal of the American Philosophical Association 6, n.º 2 (2020): 264–74. http://dx.doi.org/10.1017/apa.2019.45.
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AbstractSkeptical theism is a popular response to arguments from evil. Many hold that it undermines a key inference often used by such arguments. However, the case for skeptical theism is often kept at an intuitive level: no one has offered an explicit argument for the truth of skeptical theism. In this article, I aim to remedy this situation: I construct an explicit, rigorous argument for the truth of skeptical theism.
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De Cooman, Gert, Jasper De Bock e Márcio Alves Diniz. "Coherent Predictive Inference under Exchangeability with Imprecise Probabilities". Journal of Artificial Intelligence Research 52 (10 de janeiro de 2015): 1–95. http://dx.doi.org/10.1613/jair.4490.
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Coherent reasoning under uncertainty can be represented in a very general manner by coherent sets of desirable gambles. In a context that does not allow for indecision, this leads to an approach that is mathematically equivalent to working with coherent conditional probabilities. If we do allow for indecision, this leads to a more general foundation for coherent (imprecise-)probabilistic inference. In this framework, and for a given finite category set, coherent predictive inference under exchangeability can be represented using Bernstein coherent cones of multivariate polynomials on the simplex generated by this category set. This is a powerful generalisation of de Finetti's Representation Theorem allowing for both imprecision and indecision. We define an inference system as a map that associates a Bernstein coherent cone of polynomials with every finite category set. Many inference principles encountered in the literature can then be interpreted, and represented mathematically, as restrictions on such maps. We discuss, as particular examples, two important inference principles: representation insensitivitya strengthened version of Walley's representation invarianceand specificity. We show that there is an infinity of inference systems that satisfy these two principles, amongst which we discuss in particular the skeptically cautious inference system, the inference systems corresponding to (a modified version of) Walley and Bernard's Imprecise Dirichlet Multinomial Models (IDMM), the skeptical IDMM inference systems, and the Haldane inference system. We also prove that the latter produces the same posterior inferences as would be obtained using Haldane's improper prior, implying that there is an infinity of proper priors that produce the same coherent posterior inferences as Haldane's improper one. Finally, we impose an additional inference principle that allows us to characterise uniquely the immediate predictions for the IDMM inference systems.
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Firebaugh, Glenn. "Will Bayesian Inference Help? A Skeptical View". Sociological Methodology 25 (1995): 469. http://dx.doi.org/10.2307/271075.
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Beierle, Christoph, Christian Eichhorn, Gabriele Kern-Isberner e Steven Kutsch. "Properties and interrelationships of skeptical, weakly skeptical, and credulous inference induced by classes of minimal models". Artificial Intelligence 297 (agosto de 2021): 103489. http://dx.doi.org/10.1016/j.artint.2021.103489.
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Mills, Ethan. "Three Skepticisms in Cārvāka Epistemology: The Problem of Induction, Purandara’s Fallibilism, and Jayarāśi’s Skepticism about Philosophy". International Journal for the Study of Skepticism 12, n.º 1 (23 de dezembro de 2021): 46–71. http://dx.doi.org/10.1163/22105700-bja10029.
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Abstract The classical Indian Cārvāka (“Materialist”) tradition contains three branches with regard to the means of knowledge (pramāṇas). First, the standard Cārvākas accept a single means of knowledge, perception, supporting this view with a critique of the reliability and coherence of inference (anumāna). Second, the “more educated” Cārvākas as well as Purandara endorse a form of inference limited to empirical matters. Third, radical skeptical Cārvākas like Jayarāśi attempt to undermine all accounts or technical definitions of the means of knowledge (even perception) in order to enjoy a life free from philosophical and religious speculation. These branches respectively present something akin to David Hume’s problem of induction, endorse a fallibilistic, mitigated skepticism, and embody a thoroughgoing skepticism about philosophy itself. While all three branches are skeptics about religious matters, each branch exemplifies a different variety of epistemological skepticism.
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Beierle, Christoph, Christian Eichhorn, Gabriele Kern-Isberner e Steven Kutsch. "Properties of skeptical c-inference for conditional knowledge bases and its realization as a constraint satisfaction problem". Annals of Mathematics and Artificial Intelligence 83, n.º 3-4 (1 de fevereiro de 2018): 247–75. http://dx.doi.org/10.1007/s10472-017-9571-9.
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Komo, Christian, e Christoph Beierle. "Nonmonotonic reasoning from conditional knowledge bases with system W". Annals of Mathematics and Artificial Intelligence 90, n.º 1 (14 de dezembro de 2021): 107–44. http://dx.doi.org/10.1007/s10472-021-09777-9.
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AbstractFor nonmonotonic reasoning in the context of a knowledge base $\mathcal {R}$ R containing conditionals of the form If A then usually B, system P provides generally accepted axioms. Inference solely based on system P, however, is inherently skeptical because it coincides with reasoning that takes all ranking models of $\mathcal {R}$ R into account. System Z uses only the unique minimal ranking model of $\mathcal {R}$ R , and c-inference, realized via a complex constraint satisfaction problem, takes all c-representations of $\mathcal {R}$ R into account. C-representations constitute the subset of all ranking models of $\mathcal {R}$ R that are obtained by assigning non-negative integer impacts to each conditional in $\mathcal {R}$ R and summing up, for every world, the impacts of all conditionals falsified by that world. While system Z and c-inference license in general different sets of desirable entailments, the first major objective of this article is to present system W. System W fully captures and strictly extends both system Z and c-inference. Moreover, system W can be represented by a single strict partial order on the worlds over the signature of $\mathcal {R}$ R . We show that system W exhibits further inference properties worthwhile for nonmonotonic reasoning, like satisfying the axioms of system P, respecting conditional indifference, and avoiding the drowning problem. The other main goal of this article is to provide results on our investigations, underlying the development of system W, of upper and lower bounds that can be used to restrict the set of c-representations that have to be taken into account for realizing c-inference. We show that the upper bound of n − 1 is sufficient for capturing c-inference with respect to $\mathcal {R}$ R having n conditionals if there is at least one world verifying all conditionals in $\mathcal {R}$ R . In contrast to the previous conjecture that the number of conditionals in $\mathcal {R}$ R is always sufficient, we prove that there are knowledge bases requiring an upper bound of 2n− 1, implying that there is no polynomial upper bound of the impacts assigned to the conditionals in $\mathcal {R}$ R for fully capturing c-inference.
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Blackwell, Matthew. "A Selection Bias Approach to Sensitivity Analysis for Causal Effects". Political Analysis 22, n.º 2 (2014): 169–82. http://dx.doi.org/10.1093/pan/mpt006.
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The estimation of causal effects has a revered place in all fields of empirical political science, but a large volume of methodological and applied work ignores a fundamental fact: most people are skeptical of estimated causal effects. In particular, researchers are often worried about the assumption of no omitted variables or no unmeasured confounders. This article combines two approaches to sensitivity analysis to provide researchers with a tool to investigate how specific violations of no omitted variables alter their estimates. This approach can help researchers determine which narratives imply weaker results and which actually strengthen their claims. This gives researchers and critics a reasoned and quantitative approach to assessing the plausibility of causal effects. To demonstrate the approach, I present applications to three causal inference estimation strategies: regression, matching, and weighting.
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Maddox, Bryan. "On the Motivations of a Skeptic, and Her Practice". Peitho. Examina Antiqua 7, n.º 1 (17 de março de 2016): 229–48. http://dx.doi.org/10.14746/pea.2016.1.12.
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The aim of Pyrrhonism is deceptively simple: to achieve a state of ataraxia, of tranquility and relief from perturbation. But what is the extent of the ataraxia envisioned? Must the Skeptic admit a hard distinction between disturbances apparently related to belief and therefore subject to suspension of judgement, and extra-doxastic disturbances (e.g. everyday anxiety and frustration, or even hunger and fear) that are beyond the scope of the Skeptical method? In this paper I examine passages from Sextus’s Outlines of Pyrrhonism that indicate that such a distinction may not stand up to Skeptical scrutiny and that the Skeptical method does not only apply to “philosophical” speculative dogma or to “intellectual” perturbation, contra Barnes’s claim that the person who perceives the fewest anomalies may make “the perfect Pyrrhonist”. But I also, following Massie’s critique of unwarranted causal inferences regarding the relation between equipollence and ataraxia, distinguish cases where tarache (disturbance) presents itself as anomalous and thus lends itself to inquiry from cases where it presents itself with an apparent cause and does not provoke inquiry. Thus, though an apparently extra-doxastic disturbance may actually be rooted in unconsciously-held dogma, the Skeptic cannot demarcate a special class of potentially doxastic disturbances without employing a dogmatic psychology of her own. She must instead suspend judgment regarding the entire scope of her method, entertaining the possibility that any disturbance could be relieved through the Skeptical method. In the process, ataraxia is divested of definite parameters and the Skeptical method becomes effectively endless.
Teses / dissertações sobre o assunto "Skeptical inference"
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Carranza, Alarcón Yonatan Carlos. "Distributionally robust, skeptical inferences in supervised classification using imprecise probabilities". Thesis, Compiègne, 2020. http://www.theses.fr/2020COMP2567.
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Les décideurs sont souvent confrontés au défi de prendre des décisions précises, sans avoir aucune connaissance de la quantité d’incertitudes que celles-ci peuvent contenir, et en prenant le risque de commettre des erreurs dommageables, voire dramatiques. Dans de telles situations, où l’incertitude est plus élevée due à des informations imparfaites, il peut être plutôt utile de fournir des décisions prudentes, sous la forme d’un ensemble de solutions possibles, plus fiables. Ce travail se concentre donc sur la prise de décisions (ou inférences) sceptiques (ou prudentes) et robustes dans des problèmes de classification supervisée en utilisant des probabilités imprécises. Par robuste, nous voulons dire que nous considérons un ensemble des distributions de probabilités possibles, c'est-à-dire des probabilités imprécises, et par sceptique, nous voulons dire que nous ne considérons comme valides que les décisions étant vraies pour chaque distribution dans cet ensemble. Plus précisément, nous nous concentrons sur l'extension d’approches basée sur l'analyse discriminante gaussienne et la classification multi-étiquettes au cadre probabiliste imprécis. Concernant l'analyse discriminante gaussienne, nous proposons un nouveau classifieur imprécis qui généralise celui-ci et qui est basé sur l’inférence bayésienne robuste et un ensemble des lois de probabilités a priori. L’inclusion d’un composant imprécis dans notre approche met en évidence les décisions difficiles à prendre (c.-à-d. les observations difficiles à classifier), sur lesquelles les modèles précis font des erreurs, et permet de fournir à la place des décisions prudentes. Concernant la classification multi-étiquettes, nous nous concentrons d’abord sur la réduction de la complexité calculatoire de prendre une décision prudente sur son espace de sortie combinatoire. Pour cela, nous fournissons des justifications théoriques et des algorithmes efficaces appliqués à la fonction de coût Hamming. En outre, en relâchant l’hypothèse d’indépendance sur les étiquettes, on obtient de décisions partielles (c.-à-d. ne pas décider sur certaines étiquettes), qui généralisent l’approche classique précise (nommé « binary relevance ») en utilisant des distributions marginales imprécises. D’autre part, nous proposons aussi d’étendre le chaînage multi-étiquette classique au cadre probabiliste imprécis en fournissant deux stratégies différentes pour gérer les estimations imprécises sous la forme d’intervalles, et une nouvelle procédure d’ordre des étiquettes qui dépend des incertitudes associées aux étiquettes sélectionnées au fur et à mesure que la chaîne avanceDecision makers are often faced with making single hard decisions, without having any knowledge of the amount of uncertainties contained in them, and taking the risk of making damaging, if not dramatic, mistakes. In such situations, where the uncertainty is higher due to imperfect information, it may be useful to provide set-valued but more reliable decisions. This works thus focuses on making distributionally robust, skeptical inferences (or decisions) in supervised classification problems using imprecise probabilities. By distributionally robust, we mean that we consider a set of possible probability distributions, i.e. imprecise probabilities, and by skeptical we understand that we consider as valid only those inferences that are true for every distribution within this set. Specifically, we focus on extending the Gaussian discriminant analysis and multilabel classification approaches to the imprecise probabilistic setting. Regarding to Gaussian discriminant analysis, we extend it by proposing a new imprecise classifier, considering the imprecision as part of its basic axioms, based on robust Bayesian analysis and near-ignorance priors. By including an imprecise component in the model, our proposal highlights those hard instances on which the precise model makes mistakes in order to provide cautious decisions in the form of set-valued class, instead. Regarding to multi-label classification, we first focus on reducing the time complexity of making a cautious decision over its output space of exponential size by providing theoretical justifications and efficient algorithms applied to the Hamming loss. Relaxing the assumption of independence on labels, we obtain partial decisions, i.e. not classifying at all over some labels, which generalize the binary relevance approach by using imprecise marginal distributions. Secondly, we extend the classifierchains approach by proposing two different strategies to handle imprecise probabilityestimates, and a new dynamic, context-dependent label ordering which dynamically selects the labels with low uncertainty as the chain moves forwards
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Willot, Hénoïk. "Certified explanations of robust models". Electronic Thesis or Diss., Compiègne, 2024. http://www.theses.fr/2024COMP2812.
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Avec l'utilisation croissante des systèmes d'aide à la décision, automatisés ou semi-automatisés, en intelligence artificielle se crée le besoin de les rendre fiables et transparents pour un utilisateur final. Tandis que le rôle des méthodes d'explicabilité est généralement d'augmenter la transparence, la fiabilité peut être obtenue en fournissant des explications certifiées, dans le sens qu'elles sont garanties d'être vraies, et en considérant des modèles robustes qui peuvent s'abstenir quand l'information disponible est trop insuffisante, plutôt que de forcer une décision dans l'unique but d'éviter l'indécision. Ce dernier aspect est communément appelé "inférence sceptique". Ce travail s'inscrit dans ces considérations, en étudiant deux cas : - Le premier se focalise sur un modèle classique de décision utilisé pour intégrer de l'équité, les Sommes Pondérées Ordonnées (Ordered Weighted Averaging -- OWA) à poids décroissants. Notre principale contribution est de caractériser d'un point de vue axiomatique un ensemble convexe de ces règles, et de proposer à partir de cette caractérisation un schéma explicatif correct et complet des décisions prises qui peuvent être obtenues efficacement à partir d'heuristiques. Ce faisant, nous proposons aussi un cadre unifiant les dominances de Lorenz restreintes et généralisées, deux critères qualitatifs, et les OWA décroissants précis. - Le second se focalise sur le cas où la règle de décision est un modèle de classification obtenu à partir d'une procédure d'apprentissage sous forme d'un ensemble convexe de probabilités. Nous étudions et traitons le problème de fournir des impliquants premiers comme explication dans ce contexte, où en plus d'expliquer les préférences d'une classe sur une autre, nous avons aussi à traiter le cas où deux classes sont considérées incomparables. Nous décrivons ces problèmes de manière générale avant de les étudier en détail pour la version robuste du classifieur de Bayes NaïfWith the advent of automated or semi-automated decision systems in artificial intelligence comes the need of making them more reliable and transparent for an end-user. While the role of explainable methods is in general to increase transparency, reliability can be achieved by providing certified explanations, in the sense that those are guaranteed to be true, and by considering robust models that can abstain when having insufficient information, rather than enforcing precision for the mere sake of avoiding indecision. This last aspect is commonly referred to as skeptical inference. This work participates to this effort, by considering two cases: - The first one considers classical decision rules used to enforce fairness, which are the Ordered Weighted Averaging (OWA) with decreasing weights. Our main contribution is to fully characterise from an axiomatic perspective convex sets of such rules, and to provide together with this sound and complete explanation schemes that can be efficiently obtained through heuristics. Doing so, we also provide a unifying framework between the restricted and generalized Lorenz dominance, two qualitative criteria, and precise decreasing OWA. - The second one considers that our decision rule is a classification model resulting from a learning procedure, where the resulting model is a set of probabilities. We study and discuss the problem of providing prime implicant as explanations in such a case, where in addition to explaining clear preferences of one class over the other, we also have to treat the problem of declaring two classes as being incomparable. We describe the corresponding problems in general ways, before studying in more details the robust counter-part of the Naive Bayes Classifier
Livros sobre o assunto "Skeptical inference"
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McCain, Kevin, e Ted Poston, eds. Best Explanations. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198746904.001.0001.
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Explanatory reasoning is quite common. Not only are rigorous inferences to the best explanation used pervasively in the sciences, explanatory reasoning is virtually ubiquitous in everyday life. Despite its widespread use, inference to the best explanation is still in need of precise formulation, and it remains controversial. On the one hand, supporters of explanationism take inference to the best explanation to be a justifying form of inference—some even take all justification to be a matter of explanatory reasoning. On the other hand, critics object that inference to the best explanation is not a fundamental form of inference, and some argue that we should be skeptical of inference to the best explanation in general. This volume brings together top epistemologists and philosophers of science to explore various aspects of inference to the best explanation and the debates surrounding it. The newly commissioned chapters in this volume constitute the cutting edge of research on the role explanatory considerations play in epistemology and philosophy of science.
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Beebe, James R. Does Skepticism Presuppose Explanationism? Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198746904.003.0011.
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Explanationist (or abductivist) responses to skepticism maintain that our commonsense beliefs about the external world can be rationally preferred to skeptical hypotheses on the grounds that the former provide better explanations of our sensory experiences than the latter. This kind of response to radical skepticism has never enjoyed widespread acceptance in the epistemological community due to concerns about the epistemic merits of inference to the best explanation and appeals to the explanatory virtues. Against this tide of skepticism about explanationism, the chapter argues that traditional skeptical challenges rest upon central explanationist tenets and thus that one cannot harbor doubts about the general class of explanationist responses to skepticism while at the same time granting the force of the skeptical challenges they seek to answer. This chapter also shows how explanationist principles do a better job than epistemic closure and underdetermination principles in articulating the structure and force of skeptical challenges.
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Stegenga, Jacob. Introduction. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198747048.003.0001.
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This chapter introduces the book, describes the key arguments of each chapter, and summarizes the master argument for medical nihilism. It offers a brief survey of prominent articulations of medical nihilism throughout history, and describes the contemporary evidence-based medicine movement, to set the stage for the skeptical arguments. The main arguments are based on an analysis of the concepts of disease and effectiveness, the malleability of methods in medical research, and widespread empirical findings which suggest that many medical interventions are barely effective. The chapter-level arguments are unified by our best formal theory of inductive inference in what is called the master argument for medical nihilism. The book closes by considering what medical nihilism entails for medical practice, research, and regulation.
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Millican, Peter. Hume’s Chief Argument. Editado por Paul Russell. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199742844.013.32.
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The common tendency to characterize Hume’s philosophy as simply “skeptical,” “naturalist,” “empiricist,” or “irreligious” is a mistake. Rather, his philosophy is best seen as responding to a number of specific issues that captured his attention in the 1730s, mostly involving causation and thus explaining his particular enthusiasm for applying the Copy Principle to that idea. Other enthusiasms that shaped Book 1 of the Treatise (e.g., for sensory atomism and a crude theory of relations and mental acts) later faded, but the “Chief Argument” around causation—and causal/inductive inference—remains the consistent core of Hume’s theoretical philosophy through the Abstract and the many editions of the first Enquiry. In the Enquiry, moreover, Hume manages to tame the corrosive skepticism of the Treatise, enabling him to pursue his ambitions towards a naturalistic “science of man” while maintaining a discriminating skepticism towards aprioristic metaphysics and religion.
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Rinard, Susanna. External World Skepticism and Inference to the Best Explanation. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198746904.003.0013.
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The chapter presents three problems for IBE responses to skepticism. First, that the external world skeptic should also be a skeptic about the past. IBE responses that appeal to features of our experiences over time—such as their continuity or regularity—will be dialectically ineffective against such a skeptic, since they suspend judgment on propositions about their past experiences. Second, the chapter raises doubts about the claim that postulating external, mind-independent physical objects is the best way to explain our experiences. It is suggested that an idealist alternative may constitute an even better explanation. Finally, the chapter outlines what is, in the author’s view, the central problem for IBE responses to skepticism by formulating a principle in the spirit of the principle of indifference, and using it to make a case for the claim that explanatory goodness is not a guide to the truth.
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Johnsen, Bredo. David Hume. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190662776.003.0005.
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In this chapter the author presents Hume’s “skeptical” argument for the conclusion that there is no rational link between our observational and memorial/observational knowledge of the world and our theories about it, and defends it at length against the objection that it fails to consider probabilistic connections between evidence and theory. The author also defends Hume’s claim that our most elementary inferences are not made by any process of reasoning, but by habit and custom, against the charge that it fails to solve the problem of the missing rational link. His critics have misunderstood his claim, which is simply to have identified the means by which we arrive at the conclusions of those inferences. The author then presents Hume’s solution to the problem they have in mind, namely how any of our inductive inferences are justified: reflective equilibrium theory.
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Kornblith, Hilary. Scientific Epistemology. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780197609552.001.0001.
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This book provides an introduction to a scientifically informed approach to epistemological questions. Theories of knowledge are often motivated by the need to respond to skepticism. The skeptic presents an argument which seems to show that knowledge is impossible, and a theory of knowledge is called upon to show, contrary to the skeptic, how knowledge is indeed possible. Traditional epistemologies, however, do not draw on the sciences in providing their response to skepticism. The approach taken here, however, shows how an epistemology which is informed by the sciences offers an especially illuminating understanding of the nature of knowledge and what makes it possible. Along the way, a distinctive methodology for philosophy is defended, as is an approach to understanding how inference is conducive to knowledge which highlights various structural similarities between the workings of our perceptual systems and native inferential mechanisms. A perspective on the human capacity to reflect on our beliefs is defended which highlights its importance in cooperative problem-solving.
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Baggett, David. Moral Arguments (actually R1 to Rn). Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190842215.003.0016.
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This chapter quickly summarizes the contours of an abductive moral argument for God’s existence. The specific moral phenomenon in question here is moral duty or obligation, Plantinga’s preferred variant for this sort of argument, considering it to be the moral fact most resistant to naturalistic analysis. Noting the distinctive features of moral obligations without domesticating or watering them down enables one to see that the best explanation needs to be more robust than what naturalistic sources alone are likely to generate. The chapter gives two versions of the argument, the deductive version and the abductive version, an inference to the best explanation. It will be asserted that the second formulation, in particular, constitutes a formidable challenge for the skeptic about God’s existence.
Capítulos de livros sobre o assunto "Skeptical inference"
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Bochman, Alexander. "Skeptical Inference Relations". In A Logical Theory of Nonmonotonic Inference and Belief Change, 163–212. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04560-2_7.
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Vahid, Hamid. "Argument from Inference to the Best Explanation (IBE)". In Epistemic Justification and the Skeptical Challenge, 181–98. London: Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230596214_10.
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Beierle, Christoph, e Steven Kutsch. "Regular and Sufficient Bounds of Finite Domain Constraints for Skeptical C-Inference". In Advances in Artificial Intelligence: From Theory to Practice, 477–87. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60042-0_52.
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Beierle, Christoph, Christian Eichhorn e Gabriele Kern-Isberner. "Skeptical Inference Based on C-Representations and Its Characterization as a Constraint Satisfaction Problem". In Lecture Notes in Computer Science, 65–82. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30024-5_4.
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Skyrms, Brian. "Evolution of Inference". In Dynamics in Human and Primate Societies. Oxford University Press, 2000. http://dx.doi.org/10.1093/oso/9780195131673.003.0009.
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Rousseau began his discussion of the origin of language with a paradox that echoes through modern philosophy of language. How can we explain the genesis of speech without presupposing speech, reference without presupposing reference, meaning without presupposing meaning? A version of this paradox forms the basis of Quine's attack on the logical empiricist doctrine that logic derives its warrant from conventions of meaning—that logical truths are true and logical inferences are valid by virtue of such conventions. Quine raised the general skeptical question of how conventions of language could be established without preexisting language, as well as calling attention to more specific skeptical circularities. If conventions of logic are to be set up by explicit definition, or by axioms, must we not presuppose logic to unpack those conventions? David Lewis (1969) sought to answer these skeptical doubts within a game theoretical framework in his book, Convention. This account contains fundamental new insights, and I regard it as a major advance in the theory of meaning. Lewis sees a convention as being a special kind of strict Nash equilibrium in a game that models the relevant social interaction. To say that a convention is a Nash equilibrium is to say that if an individual deviates from a convention which others observe, he is no better off for that. To say that it is a strict Nash equilibrium is to say that he is actually worse off. To this, Lewis adds the additional requirement that an individual unilateral deviation makes everyone involved in the social interaction worse off, so that it is in the common interest to avoid such deviations. A theory of convention must answer two fundamental questions: how do we arrive at conventions?, and by virtue of what considerations do conventions remain in force? Within Lewis' game-theoretic setting, these questions become, respectively, the problems of equilibrium selection and equilibrium maintenance. On the face of it, the second problem may seem to have a trivial solution— the equilibrium is maintained because it is an equilibrium! No one has an incentive to deviate.
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Ali, Arden. "Manifestations of Virtue". In Oxford Studies in Normative Ethics Volume 10, 229–54. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198867944.003.0011.
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Few philosophers endorse a virtue theory of praiseworthiness. The widespread aversion to any virtue theory of moral worth rests chiefly on a skeptical argument that emphasizes the fact that praiseworthy acts can be performed by people who lack the relevant virtue. This chapter studies this skeptical argument closely. The response from virtue theorists has been to reject the premise of the argument by denying that someone can be fully praiseworthy for an act without possessing the relevant virtue. This chapter claims that this reply is unlikely to succeed. In its place, it argues that the skeptic’s core premise has been misleadingly characterized and used to conceal a questionable inference. The chapter concludes that it is possible for the virtue theory of praiseworthiness to escape the grip of the skeptical argument.
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De Pierris, Graciela. "Hume’s Skeptical Treatment of the Causal Inductive Inference". In Ideas, Evidence, and Method, 197–258. Oxford University Press, 2015. http://dx.doi.org/10.1093/acprof:oso/9780198716785.003.0005.
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Bergmann, Michael. "Inferential Anti-skepticism about Perception". In Radical Skepticism and Epistemic Intuition, 35–56. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192898487.003.0003.
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This chapter examines multiple kinds of deductive and nondeductive anti-skeptical arguments from our sensory experience to the likely truth of our perceptual beliefs based on that evidence and finds them all wanting. In the first two sections, it briefly considers deductive anti-skeptical arguments (of the theological and transcendental variety), inductive anti-skeptical arguments from past correlations of sensory experience with true perceptual beliefs based on it, and anti-skeptical arguments based on a priori knowledge of probabilistic principles saying that our sensory evidence for our perceptual beliefs makes probable the truth of those beliefs. In the final three sections, the focus turns to abductive or inference to the best explanation (IBE) arguments, which are currently the most popular anti-skeptical arguments. IBE anti-skeptical arguments conclude that our sensory experience, or some feature of it, is best explained by the truth of our perceptual beliefs. These three sections argue that we lack good reasons for thinking that our sensory experience is better explained by a Standard Hypothesis (saying that the world is approximately as it seems) than by a skeptical hypothesis, such as the hypothesis that a deceptive demon wants to mislead us into falsely believing the world is as it seems.
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Brown, James L. D. "Conceptual Role Expressivism and Defective Concepts". In Oxford Studies in Metaethics, Volume 17, 225–53. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780192865601.003.0009.
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Chapter 9 examines the general prospects for conceptual role expressivism, expressivist theories that embrace conceptual role semantics. It has two main aims. The first aim is to provide a general characterization of the view. The second aim is to raise a challenge for the general view. The challenge is to explain why normative concepts are not a species of defective concepts, where defective concepts are those that cannot meaningfully embed and participate in genuine inference. After rejecting existing attempts to answer the challenge, the chapter proposes an alternative solution. However, the solution leaves conceptual role expressivism a far less distinctive and interesting position than its proponents claim. The chapter concludes that we should be skeptical about how much expressivists gain by appealing to conceptual role semantics.
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Bergmann, Michael. "Underdetermination and Perceptual Skepticism". In Radical Skepticism and Epistemic Intuition, 15–34. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192898487.003.0002.
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This chapter motivates narrowing the book’s focus to a particular kind of argument for perceptual skepticism (the underdetermination argument) and to two main kinds of response to it (inferential anti-skepticism and noninferential anti-skepticism). The first half of the chapter sets aside skeptical arguments (e.g. closure-based arguments) and responses to them (e.g. contextualism, contrastivism, and closure-denial) that overestimate skepticism’s appeal by taking for granted that we don’t know that skeptical hypotheses are false. It also sets aside disjunctivist and “knowledge first” responses to skepticism, both of which underestimate skepticism’s appeal by rejecting the intuitions supporting the New Evil Demon Problem. The second half of the chapter highlights the relative strength of underdetermination arguments for perceptual skepticism, according to which our sensory evidence underdetermines the truth of our perceptual beliefs based on it. This underdetermination problem requires us to be able to infer the likely truth of our perceptual beliefs via good arguments from our sensory evidence, if our perceptual beliefs are to be justified. Given that we aren’t able to make such inferences, the underdetermination argument concludes that our perceptual beliefs aren’t justified. The inferential anti-skeptic’s response insists that we are able to make such inferences. The noninferential anti-skeptic’s response says that, despite the underdetermination problem, our perceptual beliefs can be justified even if we aren’t able to infer their likely truth via good arguments from our sensory evidence.
Trabalhos de conferências sobre o assunto "Skeptical inference"
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Rudinger, Rachel, Vered Shwartz, Jena D. Hwang, Chandra Bhagavatula, Maxwell Forbes, Ronan Le Bras, Noah A. Smith e Yejin Choi. "Thinking Like a Skeptic: Defeasible Inference in Natural Language". In Findings of the Association for Computational Linguistics: EMNLP 2020. Stroudsburg, PA, USA: Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.findings-emnlp.418.
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