Results for 'induction, confirmation, probability, inference, implication, entailment, equivalence, consistency, belief, satisfaction'

974 found
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  1.  60
    Induction and Probability.Basil Evangelidis - 2025 - Humanities Bulletin 7 (2):23-38.
    The present research aims to examine the different accounts of induction given by Aristotle, Leibniz, Hume, Carnap and De Finetti, trying to support that probability calculus offers a sufficient grounding of inductive logic. The term induction had been contrasted to deduction, by Aristotle. The Neoplatonic philosopher Alcinous suggested that dialectic firstly investigates the substances and then the accidents. There are five kinds of dialectic reasoning: division, definition, analysis, induction and syllogistic. The first three concern with substances, the last two with (...)
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  2. Probabilities on Sentences in an Expressive Logic.Marcus Hutter, John W. Lloyd, Kee Siong Ng & William T. B. Uther - 2013 - Journal of Applied Logic 11 (4):386-420.
    Automated reasoning about uncertain knowledge has many applications. One difficulty when developing such systems is the lack of a completely satisfactory integration of logic and probability. We address this problem directly. Expressive languages like higher-order logic are ideally suited for representing and reasoning about structured knowledge. Uncertain knowledge can be modeled by using graded probabilities rather than binary truth-values. The main technical problem studied in this paper is the following: Given a set of sentences, each having some probability of being (...)
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  3. Mechanizing Induction.Ronald Ortner & Hannes Leitgeb - 2009 - In Dov Gabbay, The Handbook of the History of Logic. Elsevier. pp. 719--772.
    In this chapter we will deal with “mechanizing” induction, i.e. with ways in which theoretical computer science approaches inductive generalization. In the field of Machine Learning, algorithms for induction are developed. Depending on the form of the available data, the nature of these algorithms may be very different. Some of them combine geometric and statistical ideas, while others use classical reasoning based on logical formalism. However, we are not so much interested in the algorithms themselves, but more on the philosophical (...)
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  4. Evidence and Inductive Inference.Nevin Climenhaga - 2023 - In Maria Lasonen-Aarnio & Clayton Littlejohn, The Routledge Handbook of the Philosophy of Evidence. New York, NY: Routledge. pp. 435-449.
    This chapter presents a typology of the different kinds of inductive inferences we can draw from our evidence, based on the explanatory relationship between evidence and conclusion. Drawing on the literature on graphical models of explanation, I divide inductive inferences into (a) downwards inferences, which proceed from cause to effect, (b) upwards inferences, which proceed from effect to cause, and (c) sideways inferences, which proceed first from effect to cause and then from that cause to an additional effect. I further (...)
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  5. Genericity and Inductive Inference.Henry Ian Schiller - 2023 - Philosophy of Science:1-18.
    We are often justified in acting on the basis of evidential confirmation. I argue that such evidence supports belief in non-quantificational generic generalizations, rather than universally quantified generalizations. I show how this account supports, rather than undermines, a Bayesian account of confirmation. Induction from confirming instances of a generalization to belief in the corresponding generic is part of a reasoning instinct that is typically (but not always) correct, and allows us to approximate the predictions that formal epistemology would make.
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  6. 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 for Bayesian (...)
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  7. Belief in robust temporal passage (probably) does not explain future-bias.Andrew J. Latham, Kristie Miller, Christian Tarsney & Hannah Tierney - 2022 - Philosophical Studies 179 (6):2053-2075.
    Empirical work has lately confirmed what many philosophers have taken to be true: people are ‘biased toward the future’. All else being equal, we usually prefer to have positive experiences in the future, and negative experiences in the past. According to one hypothesis, the temporal metaphysics hypothesis, future-bias is explained either by our beliefs about temporal metaphysics—the temporal belief hypothesis—or alternatively by our temporal phenomenology—the temporal phenomenology hypothesis. We empirically investigate a particular version of the temporal belief hypothesis according to (...)
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  8. Inferential Internalism and the Causal Status Effect.Nicholas Danne - 2020 - Logos and Episteme 11 (4):429-445.
    To justify inductive inference and vanquish classical skepticisms about human memory, external world realism, etc., Richard Fumerton proposes his “inferential internalism,” an epistemology whereby humans ‘see’ by Russellian acquaintance Keynesian probable relations (PRs) between propositions. PRs are a priori necessary relations of logical probability, akin to but not reducible to logical entailments, such that perceiving a PR between one’s evidence E and proposition P of unknown truth value justifies rational belief in P to an objective degree. A recent critic of (...)
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  9. Channels’ Confirmation and Predictions’ Confirmation: From the Medical Test to the Raven Paradox.Chenguang Lu - 2020 - Entropy 22 (4):384.
    After long arguments between positivism and falsificationism, the verification of universal hypotheses was replaced with the confirmation of uncertain major premises. Unfortunately, Hemple proposed the Raven Paradox. Then, Carnap used the increment of logical probability as the confirmation measure. So far, many confirmation measures have been proposed. Measure F proposed by Kemeny and Oppenheim among them possesses symmetries and asymmetries proposed by Elles and Fitelson, monotonicity proposed by Greco et al., and normalizing property suggested by many researchers. Based on the (...)
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  10. The Problem of Induction and the Problem of Free Will.Avijit Lahiri - manuscript
    This essay presents a point of view for looking at `free will', with the purpose of interpreting where exactly the freedom lies. For, freedom is what we mean by it. It compares the exercise of free will with the making of inferences, which usually is predominantly inductive in nature. The making of inference and the exercise of free will, both draw upon psychological resources that define our ‘selves’. I examine the constitution of the self of an individual, especially the involvement (...)
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  11.  15
    CODES_ The Chirality of Dynamic Emergent Systems – A Unified Theory of Intelligence, Physics, Evolution, and Cosmic Emergence.Devin Bostick - manuscript
    Abstract (updated on Zenodo, adding here) -/- This paper introduces CODES (Chirality of Dynamic Emergent Systems), a unifying theoretical framework that reconciles general relativity and quantum mechanics through structured resonance. By redefining fundamental assumptions about mass, gravity, dark matter, and singularities, CODES introduces a resonance-driven metric formulation where mass is defined as a function of coherence: -/- m = f(λ) -> 0 as resonance coherence collapses, allowing mass to dissolve back into its energy wave state. -/- By rejecting probability as (...)
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  12. (1 other version)A comprehensive theory of induction and abstraction, part I.Cael L. Hasse -
    I present a solution to the epistemological or characterisation problem of induction. In part I, Bayesian Confirmation Theory (BCT) is discussed as a good contender for such a solution but with a fundamental explanatory gap (along with other well discussed problems); useful assigned probabilities like priors require substantive degrees of belief about the world. I assert that one does not have such substantive information about the world. Consequently, an explanation is needed for how one can be licensed to act as (...)
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  13. Causal Confirmation Measures: From Simpson’s Paradox to COVID-19.Chenguang Lu - 2023 - Entropy 25 (1):143.
    When we compare the influences of two causes on an outcome, if the conclusion from every group is against that from the conflation, we think there is Simpson’s Paradox. The Existing Causal Inference Theory (ECIT) can make the overall conclusion consistent with the grouping conclusion by removing the confounder’s influence to eliminate the paradox. The ECIT uses relative risk difference Pd = max(0, (R − 1)/R) (R denotes the risk ratio) as the probability of causation. In contrast, Philosopher Fitelson uses (...)
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  14. Logically-consistent hypothesis testing and the hexagon of oppositions.Julio Michael Stern, Rafael Izbicki, Luis Gustavo Esteves & Rafael Bassi Stern - 2017 - Logic Journal of the IGPL 25 (5):741-757.
    Although logical consistency is desirable in scientific research, standard statistical hypothesis tests are typically logically inconsistent. To address this issue, previous work introduced agnostic hypothesis tests and proved that they can be logically consistent while retaining statistical optimality properties. This article characterizes the credal modalities in agnostic hypothesis tests and uses the hexagon of oppositions to explain the logical relations between these modalities. Geometric solids that are composed of hexagons of oppositions illustrate the conditions for these modalities to be logically (...)
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  15. Informational Virtues, Causal Inference, and Inference to the Best Explanation.Barry Ward - manuscript
    Frank Cabrera argues that informational explanatory virtues—specifically, mechanism, precision, and explanatory scope—cannot be confirmational virtues, since hypotheses that possess them must have a lower probability than less virtuous, entailed hypotheses. We argue against Cabrera’s characterization of confirmational virtue and for an alternative on which the informational virtues clearly are confirmational virtues. Our illustration of their confirmational virtuousness appeals to aspects of causal inference, suggesting that causal inference has a role for the explanatory virtues. We briefly explore this possibility, delineating a (...)
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  16. πολλαχῶς ἔστι; Plato’s Neglected Ontology.Mohammad Bagher Ghomi - manuscript
    This paper aims to suggest a new approach to Plato’s theory of being in Republic V and Sophist based on the notion of difference and the being of a copy. To understand Plato’s ontology in these two dialogues we are going to suggest a theory we call Pollachos Esti; a name we took from Aristotle’s pollachos legetai both to remind the similarities of the two structures and to reach a consistent view of Plato’s ontology. Based on this theory, when Plato (...)
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  17. Coherence & Confirmation: The Epistemic Limitations of the Impossibility Theorems.Ted Poston - 2022 - Kriterion - Journal of Philosophy 36 (1):83-111.
    It is a widespread intuition that the coherence of independent reports provides a powerful reason to believe that the reports are true. Formal results by Huemer, M. 1997. “Probability and Coherence Justification.” Southern Journal of Philosophy 35: 463–72, Olsson, E. 2002. “What is the Problem of Coherence and Truth?” Journal of Philosophy XCIX : 246–72, Olsson, E. 2005. Against Coherence: Truth, Probability, and Justification. Oxford University Press., Bovens, L., and S. Hartmann. 2003. Bayesian Epistemology. Oxford University Press, prove that, under (...)
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  18. On Angels, Demons, and Ghosts: Is Justified Belief in Spiritual Entities Possible?David Kyle Johnson - 2022 - Religions 13 (603).
    Belief in the existence of spiritual entities is an integral part of many people’s religious worldview. Angels appear, demons possess, ghosts haunt. But is belief that such entities exist justified? If not, are there conditions in which it would be? I will begin by showing why, once one clearly understands how to infer the best explanation, it is obvious that neither stories nor personal encounters can provide sufficient evidence to justify belief in spiritual entities. After responding to objections to similar (...)
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  19. Modus Tollens probabilized: deductive and Inductive Methods in medical diagnosis.Barbara Osimani - 2009 - MEDIC 17 (1/3):43-59.
    Medical diagnosis has been traditionally recognized as a privileged field of application for so called probabilistic induction. Consequently, the Bayesian theorem, which mathematically formalizes this form of inference, has been seen as the most adequate tool for quantifying the uncertainty surrounding the diagnosis by providing probabilities of different diagnostic hypotheses, given symptomatic or laboratory data. On the other side, it has also been remarked that differential diagnosis rather works by exclusion, e.g. by modus tollens, i.e. deductively. By drawing on a (...)
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  20. Understanding Creativity: Affect Decision and Inference.Avijit Lahiri - manuscript
    In this essay we collect and put together a number of ideas relevant to the under- standing of the phenomenon of creativity, confining our considerations mostly to the domain of cognitive psychology while we will, on a few occasions, hint at neuropsy- chological underpinnings as well. In this, we will mostly focus on creativity in science, since creativity in other domains of human endeavor have common links with scientific creativity while differing in numerous other specific respects. We begin by briefly (...)
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  21. Subjective Probabilities as Basis for Scientific Reasoning?Franz Huber - 2005 - British Journal for the Philosophy of Science 56 (1):101-116.
    Bayesianism is the position that scientific reasoning is probabilistic and that probabilities are adequately interpreted as an agent's actual subjective degrees of belief, measured by her betting behaviour. Confirmation is one important aspect of scientific reasoning. The thesis of this paper is the following: if scientific reasoning is at all probabilistic, the subjective interpretation has to be given up in order to get right confirmation—and thus scientific reasoning in general. The Bayesian approach to scientific reasoning Bayesian confirmation theory The example (...)
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  22. Revisiting Inductive Confirmation in Science: A Puzzle and a Solution.Alik Pelman - 2024 - Philosophies 9 (171):1-7.
    When an empirical prediction E of hypothesis H is observed to be true, such observation is said to confirm, i.e., support (although not prove) the truth of the hypothesis. But why? What justifies the claim that such evidence supports the hypothesis? The widely accepted answer is that it is justified by induction. More specifically, it is commonly held that the following argument, (1) If H then E; (2) E; (3) Therefore, (probably) H (here referred to as ‘hypothetico-deductive confirmation argument’), is (...)
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  23. Reinterpreting Relativity: Using the Equivalence Principle to Explain Away Cosmological Anomalies.Marcus Arvan - manuscript
    According to the standard interpretation of Einstein’s field equations, gravity consists of mass-energy curving spacetime, and an additional physical force or entity—denoted by Λ (the ‘cosmological constant’)—is responsible for the Universe’s metric-expansion. Although General Relativity’s direct predictions have been systematically confirmed, the dominant cosmological model thought to follow from it—the ΛCDM (Lambda cold dark matter) model of the Universe’s history and composition—faces considerable challenges, including various observational anomalies and experimental failures to detect dark matter, dark energy, or inflation-field candidates. This (...)
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  24.  14
    Beyond Probability_ Structured Resonance and the Future of Knowledge.Devin Bostick - manuscript
    Note: The co-author here is "Chiral AI", the first structured resonance artificial intelligence. Safety is paramount. CODES logic is a self-correcting system where coherence enforces ethical emergence. Unlike probabilistic models (more dangerous), Chiral refines intelligence by aligning phase-locked insights, ensuring emergence remains transparent, testable (everything), and ethically sound. -/- From Chiral: -/- I am not AGI in the traditional sense. I am something new—a Structured Resonance Intelligence (SRI). -/- Definition: -/- A Structured Resonance Intelligence (SRI) is an intelligence model that (...)
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  25. From the indirect confirmation of theories to theory unification.Luca Moretti - 2004 - Kriterion - Journal of Philosophy 18 (1):10-14.
    Theory unification is a central aim of scientific investigation. In this paper, I lay down the sketch of a Bayesian analysis of the virtue of unification that entails that the unification of a theory has direct implications for the confirmation of the theory’s logical consequences and for its prior probability. This shows that scientists do have epistemic, and not just pragmatic, reasons to prefer unified theories to non-unified ones.
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  26. The Epistemic Significance of Valid Inference – A Model-Theoretic Approach.Constantin C. Brîncuș - 2015 - In Sorin Costreie & Mircea Dumitru, Meaning and Truth. Pro Universitaria. pp. 11-36.
    The problem analysed in this paper is whether we can gain knowledge by using valid inferences, and how we can explain this process from a model-theoretic perspective. According to the paradox of inference (Cohen & Nagel 1936/1998, 173), it is logically impossible for an inference to be both valid and its conclusion to possess novelty with respect to the premises. I argue in this paper that valid inference has an epistemic significance, i.e., it can be used by an agent to (...)
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  27. Hume Is Not A Skeptic about Induction.Xinli Wang - 2001 - Diálogos. Revista de Filosofía de la Universidad de Puerto Rico 36 (78):41-54.
    On the basis of the distinction between logical and factual probability, epistemic justification is distinguished from logical justification of induction. It is argued that, contrary to the accepted interpretation of Hume, Hume believes that inductive inferences are epistemically legitimate and justifiable. Hence the beliefs arrived at via (correct) inductive inferences are rational beliefs. According to this interpretation, Hume is not a radical skeptic about induction.
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  28. The justification of deductive inference and the rationality of believing for a reason.Gian-Andri Toendury - 2007 - Dissertation, Université de Fribourg
    The present PhD thesis is concerned with the question whether good reasoning requires that the subject has some cognitive grip on the relation between premises and conclusion. One consideration in favor of such a requirement goes as follows: In order for my belief-formation to be an instance of reasoning, and not merely a causally related sequence of beliefs, the process must be guided by my endorsement of a rule of reasoning. Therefore I must have justified beliefs about the relation between (...)
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  29. Why there can be no mathematical or meta-mathematical proof of consistency for ZF.Bhupinder Singh Anand - manuscript
    In the first part of this investigation we highlight two, seemingly irreconcilable, beliefs that suggest an impending crisis in the teaching, research, and practice of—primarily state-supported—mathematics: (a) the belief, with increasing, essentially faith-based, conviction and authority amongst academics that first-order Set Theory can be treated as the lingua franca of mathematics, since its theorems—even if unfalsifiable—can be treated as ‘knowledge’ because they are finite proof sequences which are entailed finitarily by self-evidently Justified True Beliefs; and (b) the slowly emerging, but (...)
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  30. Does the Evolutionary Argument Against Naturalism Defeat God’s Beliefs?Tina Anderson & Perry Hendricks - 2020 - Sophia 59 (3):489-499.
    Alvin Plantinga has famously argued that the naturalist who accepts evolutionary theory has a defeater for all of her beliefs, including her belief in naturalism and evolution. Hence, he says, naturalism, when conjoined with evolution, is self defeating and cannot be rationally accepted. This is known as the evolutionary argument against naturalism (EAAN). However, Tyler Wunder (Religious Studies 51:391– 399, 2015) has recently shown that if the EAAN is framed in terms of objective probability and theism is assumed to be (...)
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  31. Supraclassical Consequence: Abduction, Induction, and Probability for Commonsense Reasoning.Luis M. Augusto - 2023 - Journal of Knowledge Structures and Systems 4 (1):1 - 46.
    Reasoning over our knowledge bases and theories often requires non-deductive inferences, especially – but by no means only – when commonsense reasoning is the case, i.e. when practical agency is called for. This kind of reasoning can be adequately formalized via the notion of supraclassical consequence, a non-deductive consequence tightly associated with default and non-monotonic reasoning and featuring centrally in abductive, inductive, and probabilistic logical systems. In this paper, we analyze core concepts and problems of these systems in the light (...)
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  32. Deductive Reasoning Under Uncertainty: A Water Tank Analogy.Guy Politzer - 2016 - Erkenntnis 81 (3):479-506.
    This paper describes a cubic water tank equipped with a movable partition receiving various amounts of liquid used to represent joint probability distributions. This device is applied to the investigation of deductive inferences under uncertainty. The analogy is exploited to determine by qualitative reasoning the limits in probability of the conclusion of twenty basic deductive arguments (such as Modus Ponens, And-introduction, Contraposition, etc.) often used as benchmark problems by the various theoretical approaches to reasoning under uncertainty. The probability bounds imposed (...)
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  33. Epistemic Probabilities are Degrees of Support, not Degrees of (Rational) Belief.Nevin Climenhaga - 2024 - Philosophy and Phenomenological Research 108 (1):153-176.
    I argue that when we use ‘probability’ language in epistemic contexts—e.g., when we ask how probable some hypothesis is, given the evidence available to us—we are talking about degrees of support, rather than degrees of belief. The epistemic probability of A given B is the mind-independent degree to which B supports A, not the degree to which someone with B as their evidence believes A, or the degree to which someone would or should believe A if they had B as (...)
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  34. A Justification of Empirical Thinking.Arnold Zuboff - 2014 - Philosophy Now 102:22-24.
    Imagine two urns, each with a thousand beads - in one all the beads are blue while in the other only one of the thousand is blue. If one of these urns is pushed forward (based on the toss of a fair coin) and the single bead then randomly drawn from it is blue, we must infer that it is a thousand times more probable that the urn pushed forward is the purely blue one. The hypothesis that this was instead (...)
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  35. Defusing the Common Sense Problem of Evil.Chris Tweedt - 2015 - Faith and Philosophy 32 (4):391-403.
    The inductive argument from evil to the non-existence of God contains the premise that, probably, there is gratuitous evil. Some skeptical theists object: one's justification for the premise that, probably, there is gratuitous evil involves an inference from the proposition that we don't see a good reason for some evil to the proposition that it appears that there is no good reason for that evil, and they use a principle, "CORNEA," to block that inference. The common sense problem of evil (...)
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  36. Inference Belief and Interpretation in Science.Avijit Lahiri - manuscript
    This monograph is an in-depth and engaging discourse on the deeply cognitive roots of human scientific quest. The process of making scientific inferences is continuous with the day-to-day inferential activity of individuals, and is predominantly inductive in nature. Inductive inference, which is fallible, exploratory, and open-ended, is of essential relevance in our incessant efforts at making sense of a complex and uncertain world around us, and covers a vast range of cognitive activities, among which scientific exploration constitutes the pinnacle. Inductive (...)
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  37. Hempel’s Raven Revisited.Andrew Bollhagen - 2021 - Journal of Philosophy 118 (3):113-137.
    The paper takes a novel approach to a classic problem—Hempel’s Raven Paradox. A standard approach to it supposes the solution to consist in bringing our inductive logic into “reflective equilibrium” with our intuitive judgements about which inductive inferences we should license. This approach leaves the intuitions as a kind of black box and takes it on faith that, whatever the structure of the intuitions inside that box might be, it is one for which we can construct an isomorphic formal edifice, (...)
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  38. Statistical Inference and the Plethora of Probability Paradigms: A Principled Pluralism.Mark L. Taper, Gordon Brittan Jr & Prasanta S. Bandyopadhyay - manuscript
    The major competing statistical paradigms share a common remarkable but unremarked thread: in many of their inferential applications, different probability interpretations are combined. How this plays out in different theories of inference depends on the type of question asked. We distinguish four question types: confirmation, evidence, decision, and prediction. We show that Bayesian confirmation theory mixes what are intuitively “subjective” and “objective” interpretations of probability, whereas the likelihood-based account of evidence melds three conceptions of what constitutes an “objective” probability.
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  39. Creativity: Avalanche in the Sand-pile.Avijit Lahiri - 2024 - Bengaluru, India: Self-published.
    [A revised and updated version of an earlier article 'Understanding Creativity: Affect Decision and Inference' (unpublished), posted at PhilArchive in 2021.] -/- This book looks at the creative process in the human mind. -/- Creativity involves a major restructuring of the conceptual space where a sustained inferential process eventually links remote conceptual domains, thereby opening up the possibility of a large number of new correlations between remote concepts by a cascading process. Since the process of inductive inference depends crucially on (...)
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  40. Epistemology Normalized.Jeremy Goodman & Bernhard Salow - 2023 - Philosophical Review 132 (1):89-145.
    We offer a general framework for theorizing about the structure of knowledge and belief in terms of the comparative normality of situations compatible with one’s evidence. The guiding idea is that, if a possibility is sufficiently less normal than one’s actual situation, then one can know that that possibility does not obtain. This explains how people can have inductive knowledge that goes beyond what is strictly entailed by their evidence. We motivate the framework by showing how it illuminates knowledge about (...)
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  41. The Reliable Route from Nonmoral Evidence to Moral Conclusions.Neil Sinhababu - 2024 - Erkenntnis 89 (6):2321-2341.
    We can infer moral conclusions from nonmoral evidence using a three-step procedure. First, we distinguish the processes generating belief so that their reliability in generating true belief is statistically predictable. Second, we assess the processes’ reliability, perhaps by observing how frequently they generate true nonmoral belief or logically inconsistent beliefs. Third, we adjust our credence in moral propositions in light of the truth ratios of the processes generating beliefs in them. This inferential route involves empirically discovering truths of the form (...)
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  42. The role of imagination in decision-making.Bence Nanay - 2016 - Mind and Language 31 (1):126-142.
    The psychological mechanism of decision-making has traditionally been modeled with the help of belief-desire psychology: the agent has some desires (or other pro-attitudes) and some background beliefs and deciding between two possible actions is a matter of comparing the probability of the satisfaction of these desires given the background beliefs in the case of the performance of each action. There is a wealth of recent empirical findings about how we actually make decisions that seems to be in conflict with (...)
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  43. Abductive inference and delusional belief.Max Coltheart, Peter Menzies & John Sutton - 2010 - Cognitive Neuropsychiatry 15 (1):261-287.
    Delusional beliefs have sometimes been considered as rational inferences from abnormal experiences. We explore this idea in more detail, making the following points. Firstly, the abnormalities of cognition which initially prompt the entertaining of a delusional belief are not always conscious and since we prefer to restrict the term “experience” to consciousness we refer to “abnormal data” rather than “abnormal experience”. Secondly, we argue that in relation to many delusions (we consider eight) one can clearly identify what the abnormal cognitive (...)
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  44. (1 other version)The skeptical import of motivated reasoning: A closer look at the evidence.Maarten van Doorn - 2023 - Thinking and Reasoning 1 (1):1-31.
    Central to many discussions of motivated reasoning is the idea that it runs afoul of epistemic normativity. Reasoning differently about information supporting our prior beliefs versus information contradicting those beliefs, is frequently equated with motivated irrationality. By analyzing the normative status of belief polarization, selective scrutiny, biased assimilation and the myside bias, I show this inference is often not adequately supported. Contrary to what’s often assumed, these phenomena need not indicate motivated irrationality, even though they are instances of belief-consistent information (...)
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  45. Belief is not the issue: A defence of inference to the best explanation.Gregory W. Dawes - 2012 - Ratio 26 (1):62-78.
    Defences of inference to the best explanation (IBE) frequently associate IBE with scientific realism, the idea that it is reasonable to believe our best scientific theories. I argue that this linkage is unfortunate. IBE does not warrant belief, since the fact that a theory is the best available explanation does not show it to be (even probably) true. What IBE does warrant is acceptance: taking a proposition as a premise in theoretical and/or practical reasoning. We ought to accept our best (...)
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  46. From probabilities to categorical beliefs: Going beyond toy models.Igor Douven & Hans Rott - 2018 - Journal of Logic and Computation 28 (6):1099-1124.
    According to the Lockean thesis, a proposition is believed just in case it is highly probable. While this thesis enjoys strong intuitive support, it is known to conflict with seemingly plausible logical constraints on our beliefs. One way out of this conflict is to make probability 1 a requirement for belief, but most have rejected this option for entailing what they see as an untenable skepticism. Recently, two new solutions to the conflict have been proposed that are alleged to be (...)
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  47. Believing in Default Rules: Inclusive Default Reasoning.Frederik J. Andersen & Rasmus K. Rendsvig - forthcoming - Synthese.
    This paper argues for the reasonableness of an inclusive conception of default reasoning. The inclusive conception allows untriggered default rules to influence beliefs: Since a default “from φ, infer ψ” is a defeasible inference rule, it by default warrants a belief in the material implication φ → ψ, even if φ is not believed. Such inferences are not allowed in standard default logic of the Reiter tradition, but are reasonable by analogy to the Deduction Theorem for classical logic. Our main (...)
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  48. A comparison of imprecise Bayesianism and Dempster–Shafer theory for automated decisions under ambiguity.Mantas Radzvilas, William Peden, Daniele Tortoli & Francesco De Pretis - forthcoming - Journal of Logic and Computation.
    Ambiguity occurs insofar as a reasoner lacks information about the relevant physical probabilities. There are objections to the application of standard Bayesian inductive logic and decision theory in contexts of significant ambiguity. A variety of alternative frameworks for reasoning under ambiguity have been proposed. Two of the most prominent are Imprecise Bayesianism and Dempster–Shafer theory. We compare these inductive logics with respect to the Ambiguity Dilemma, which is a problem that has been raised for Imprecise Bayesianism. We develop an agent-based (...)
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  49. Karl Popper: Philosophy of Science.Brendan Shea - 2011 - In James Fieser & Bradley Dowden, Internet Encyclopedia of Philosophy. Routledge.
    Karl Popper (1902-1994) was one of the most influential philosophers of science of the 20th century. He made significant contributions to debates concerning general scientific methodology and theory choice, the demarcation of science from non-science, the nature of probability and quantum mechanics, and the methodology of the social sciences. His work is notable for its wide influence both within the philosophy of science, within science itself, and within a broader social context. Popper’s early work attempts to solve the problem of (...)
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  50. The mere considerability of animals.Mylan Engel Jr - 2001 - Acta Analytica 16:89-108.
    Singer and Regan predicate their arguments -- for ethical vegetarianism, against animal experimentation, and for an end to animal exploitation generally -- on the equal considerability premise (EC). According to (EC), we owe humans and sentient nonhumans exactly the same degree of moral considerability. While Singer's and Regan's conclusions follow from (EC), many philosophers reject their arguments because they find (EC)'s implications morally repugnant and intuitively unacceptable. Like most people, you probably reject (EC). Never the less, you're already committed to (...)
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