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  1. Falsification and future performance.David Balduzzi - manuscript
    We information-theoretically reformulate two measures of capacity from statistical learning theory: empirical VC-entropy and empirical Rademacher complexity. We show these capacity measures count the number of hypotheses about a dataset that a learning algorithm falsifies when it finds the classifier in its repertoire minimizing empirical risk. It then follows from that the future performance of predictors on unseen data is controlled in part by how many hypotheses the learner falsifies. As a corollary we show that empirical VC-entropy quantifies the message (...)
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  2. Falsifiable implies Learnable.David Balduzzi - manuscript
    The paper demonstrates that falsifiability is fundamental to learning. We prove the following theorem for statistical learning and sequential prediction: If a theory is falsifiable then it is learnable -- i.e. admits a strategy that predicts optimally. An analogous result is shown for universal induction.
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  3. Probability and Inductive Logic.Antony Eagle - manuscript
    Reasoning from inconclusive evidence, or ‘induction’, is central to science and any applications we make of it. For that reason alone it demands the attention of philosophers of science. This Element explores the prospects of using probability theory to provide an inductive logic, a framework for representing evidential support. Constraints on the ideal evaluation of hypotheses suggest that overall support for a hypothesis is represented by its probability in light of the total evidence, and incremental support, or confirmation, indicated by (...)
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  4. Logical vs Practical Reasons.Paul Mayer - manuscript
    For years, the European world saw millions of swans, and all of them without exception were white. If inductive reasoning is valid, one may conclude that all swans are white. However, this would be incorrect: in 1667 Dutch explorer Willem de Vlamingh observed black swans in Australia, falsifying the hypothesis that all swans are white. While often used as a cautionary tale for the use of induction, such as with Popper’s falsification principle, I want to explore a slightly different idea: (...)
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  5. Making of the Problem: Induction from Socrates to Popper.John P. McCaskey - manuscript
  6. On the general form of the Grue Paradox.Chaohui Zhuang - manuscript
    The grue paradox, also called the new riddle of induction, posed a great challenge to the common understanding about induction. This paper shows that there is a close relation between the grue paradox and the problem of conditionals. This paper presents a general form of the grue predicate. Based on the general form, this paper argues that this kind of predicates can not be used for induction and prediction.
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  7. Information, learning and falsification.David Balduzzi - 2011
    There are (at least) three approaches to quantifying information. The first, algorithmic information or Kolmogorov complexity, takes events as strings and, given a universal Turing machine, quantifies the information content of a string as the length of the shortest program producing it [1]. The second, Shannon information, takes events as belonging to ensembles and quantifies the information resulting from observing the given event in terms of the number of alternate events that have been ruled out [2]. The third, statistical learning (...)
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  8. Inductive Reasoning Involving Social Kinds.Barrett Emerick & Tyler Hildebrand - forthcoming - Journal of the American Philosophical Association:1-20.
    Most social policies cannot be defended without making inductive inferences. For example, consider certain arguments for racial profiling and affirmative action, respectively. They begin with statistics about crime or socioeconomic indicators. Next, there is an inductive step in which the statistic is projected from the past to the future. Finally, there is a normative step in which a policy is proposed as a response in the service of some goal—for example, to reduce crime or to correct socioeconomic imbalances. In comparison (...)
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  9. Theoretical Terms and Inductive Inference.Keith Lehrer - forthcoming - American Philosophical Quarterly.
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  10. Genericity and Inductive Inference.Henry Ian Schiller - forthcoming - 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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  11. Human Induction in Machine Learning: A Survey of the Nexus.Petr Spelda & Vit Stritecky - forthcoming - ACM Computing Surveys.
    As our epistemic ambitions grow, the common and scientific endeavours are becoming increasingly dependent on Machine Learning (ML). The field rests on a single experimental paradigm, which consists of splitting the available data into a training and testing set and using the latter to measure how well the trained ML model generalises to unseen samples. If the model reaches acceptable accuracy, an a posteriori contract comes into effect between humans and the model, supposedly allowing its deployment to target environments. Yet (...)
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  12. On Explaining the Success of Induction.Tom F. Sterkenburg - forthcoming - British Journal for the Philosophy of Science.
    Douven (in press) observes that Schurz's meta-inductive justification of induction cannot explain the great empirical success of induction, and offers an explanation based on computer simulations of the social and evolutionary development of our inductive practices. In this paper, I argue that Douven's account does not address the explanatory question that Schurz's argument leaves open, and that the assumption of the environment's induction-friendliness that is inherent to Douven's simulations is not justified by Schurz's argument.
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  13. Why Confirm Laws?Barry Ward - forthcoming - The British Journal for the Philosophy of Science.
    We argue that a particular approach to satisfying the broad predictive ambitions of the sciences demands law confirmation. On this approach we confirm non-nomic generalizations by confirming there are no actually realized ways of causing disconfirming cases. This gives causal generalizations a crucial role in prediction. We then show how rational judgements of relevant causal similarity can be used to confirm that causal generalizations themselves have no actual disconfirmers, providing a distinctive and clearly viable methodology for inductively confirming them. Finally, (...)
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  14. On Mentioning Belief-Formation Methods in the Sensitivity Subjunctives.Bin Zhao - forthcoming - Ergo: An Open Access Journal of Philosophy.
    According to the sensitivity account of knowledge, S knows that p only if S’s belief in p is sensitive in the sense that S would not believe that p if p were false. The sensitivity condition is usually relativized to belief-formation methods to avoid putative counterexamples. A remaining issue for the account is where methods should be mentioned in the sensitivity subjunctives. In this paper, I argue that if methods are mentioned in the antecedent, then the account is too strong (...)
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  15. Evidence and Inductive Inference.Nevin Climenhaga - 2024 - In Maria Lasonen-Aarnio & Clayton Littlejohn (eds.), 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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  16. A Little More Logical: Reasoning Well About Science, Ethics, Religion, and the Rest of Life (2nd edition).Brendan Shea - 2024 - Rochester, MN: Thoughtful Noodle Books.
    In a world filled with information overload and complex problems, the ability to think logically is a superpower. "A Little More Logical" is your guide to mastering this essential skill. This engaging and accessible open educational resource is perfect for students, teachers, and lifelong learners who want to improve their critical thinking abilities and make better decisions in all aspects of life. -/- Through a series of fun and interactive chapters, "A Little More Logical" covers a wide range of topics, (...)
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  17. A Framework for Inductive Reasoning in Model-Based Science.M. M. Barroso Rojo - 2023 - Revista de Humanidades de Valparaíso (23):259-285.
    This paper argues that the linguistic approach to analyzing induction, according to which induction is a type of inference or argument composed of statements or propositions, is unsuitable to account for scientific reasoning. Consequently, a novel approach to induction in model-based science is suggested. First, in order to show their adherence to the linguistic treatment of induction, two strategies are reviewed: (i) Carnap and Reichenbach’s attempts to justify induction and (ii) Norton’s recent material theory of induction. Second, three reasons are (...)
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  18. A Dilemma for Solomonoff Prediction.Sven Neth - 2023 - Philosophy of Science 90 (2):288-306.
    The framework of Solomonoff prediction assigns prior probability to hypotheses inversely proportional to their Kolmogorov complexity. There are two well-known problems. First, the Solomonoff prior is relative to a choice of Universal Turing machine. Second, the Solomonoff prior is not computable. However, there are responses to both problems. Different Solomonoff priors converge with more and more data. Further, there are computable approximations to the Solomonoff prior. I argue that there is a tension between these two responses. This is because computable (...)
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  19. A Framework for Inductive Reasoning in Model-Based Science.Milagros Maribel Barroso Rojo - 2023 - Revista de Humanidades de Valparaíso 23:259-285.
    This paper argues that the linguistic approach to analyzing induction, according to which induction is a type of inference or argument composed of statements or propositions, is unsuitable to account for scientific reasoning. Consequently, a novel approach to induction in model-based science is suggested. First, in order to show their adherence to the linguistic treatment of induction, two strategies are reviewed: (i) Carnap and Reichenbach’s attempts to justify induction and (ii) Norton’s recent material theory of induction. Second, three reasons are (...)
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  20. Theory, Evidence, Data: Themes from George E. Smith.Marius Stan & Christopher Smeenk - 2023 - Springer.
    A volume of papers inspired by the work of George E. Smith on confirmation and evidence in advanced science—from Newton's gravitation theory to the physics of molecules.
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  21. The Independence Solution to Grue.Jared Warren - 2023 - Philosophical Studies 180 (4):1305-1326.
    The paper presents a comprehensive solution to the new riddle of induction. Gruesome induction is blocked because “grue” is not independent of our sampling and observation methods. Before presenting my theory, I critically survey previous versions of what I call the “independence strategy”, tracing the strategy to three different papers from the 1970s by (respectively) Wilkerson, Moreland, and Jackson. Next I critically examine recent approaches by Okasha, Godfrey-Smith, Schramm, and Freitag. All of these approaches have their virtues, but none of (...)
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  22. Answering More of the Same: A Reply to Nahm.Keith Augustine - 2022 - Journal of Scientific Exploration 36 (4):794-808.
    Michael Nahm's preceding commentary accuses me of seven misrepresentations. One of these is an acknowledged good-faith error about a peripheral detail, while the remaining six are demonstrably accurate descriptions of Nahm's statements. At the same time, Nahm verifiably misrepresents me frequently and intentionally over issues that he takes to be consequential, which is a much more serious offense. All authors should call out when an interlocutor get their points wrong, but only when they can definitively back up the charge. Where (...)
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  23. How Not to Do Survival Research: Reflections on the Bigelow Institute Essay Competition.Keith Augustine - 2022 - Journal of Scientific Exploration 36 (2):366-398.
    The recent Bigelow Institute contest rewarding the "best" evidence for life after death epitomizes much of what's wrong with the current state of survival research, its participants constituting a who's who list of contemporary survival researchers. Cases that are regularly hyped as among the best evidence for an afterlife are all too often easily susceptible to normal explanations--if only survival researchers would give them a chance. The consistently negative results of 121 years of experimental survival research ought to have spurred (...)
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  24. Formal Schemas of Induction as Models.Vlademire Kevin D. Bumatay - 2022 - Synthese 200 (6):1-33.
    What is the relation or connection between formalizations of induction and the actual inductive inferences of scientists? Building from recent works in the philosophy of logic, this paper argues that these formalizations of induction are best viewed as models and not literal descriptions of inductive inferences in science. Three arguments are put forward to support this claim. First, I argue that inductive support is the kind of phenomenon that can be justifiably modeled. Second, I argue that these formalizations have the (...)
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  25. The Reception of Positivism in Whewell, Mill and Brentano.Arnaud Dewalque - 2022 - In Ion Tanasescu, Alexandru Bejinariu, Susan Krantz Gabriel & Constantin Stoenescu (eds.), Brentano and the Positive Philosophy of Comte and Mill: With Translations of Original Writings on Philosophy as Science by Franz Brentano. Berlin: De Gruyter.
    This article compares and contrasts the reception of Comte’s positivism in the works of William Whewell, John Stuart Mill and Franz Brentano. It is argued that Whewell’s rejection of positivism derives from his endorsement of a constructivist account of the inductive sciences, while Mill and Brentano’s sympathies for positivism are connected to their endorsement of an empiricist account. The mandate of the article is to spell out the chief differences between these two rival accounts. In the last, conclusive section, Whewell’s (...)
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  26. Beyond the BICS Essay Contest: Envisioning a More Rigorous Preregistered Survival Study.Etienne LeBel, Keith Augustine & Adam Rock - 2022 - Journal of Scientific Exploration 36 (2):436-447.
    Prior experimental studies of anomalous information reception (AIR) have been touted as strong evidence for postmortem survival of consciousness yet are plagued by several methodological weaknesses that preclude clear evidence of positive results. The present team provides an adversarial collaboration to identify and compensate for the major limitations of these previous approaches. We outline a more rigorous preregistered study design that eliminates or minimizes researcher bias in (a) data cleaning and (b) statistical analysis. Obtaining positive results with our recommended design (...)
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  27. Evidence and analogy in Archaeoastronomy.Francesco Nappo, Giulio Magli & Giovanni Valente - 2022 - Synthese 200 (6):1-25.
    This paper addresses the role of analogical reasoning in archaeoastronomy - the discipline which studies the connections between the ancient monuments and the heavens. Archaeoastronomy is a highly interdisciplinary science, placed at the border between the humanities – especially archaeology – and the scientific approach to cultural heritage. As a consequence, its scientific foundations are a delicate matter. We plan to investigate here the question of what constitutes the evidence for analogical inferences in archaeoastronomy and to what extent one can (...)
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  28. Speed-Optimal Induction and Dynamic Coherence.Michael Nielsen & Eric Wofsey - 2022 - British Journal for the Philosophy of Science 73 (2):439-455.
    A standard way to challenge convergence-based accounts of inductive success is to claim that they are too weak to constrain inductive inferences in the short run. We respond to such a challenge by answering some questions raised by Juhl (1994). When it comes to predicting limiting relative frequencies in the framework of Reichenbach, we show that speed-optimal convergence—a long-run success condition—induces dynamic coherence in the short run.
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  29. Explanatory reasoning in the material theory of induction.William Peden - 2022 - Metascience 31 (3):303-309.
    In his recent book, John Norton has created a theory of inference to the best explanation, within the context of his "material theory of induction". I apply it to the problem of scientific explanations that are false: if we want the theories in our explanations to be true, then why do historians and scientists often say that false theories explained phenomena? I also defend Norton's theory against some possible objections.
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  30. The Material Theory of Induction at the Frontiers of Science.William Peden - 2022 - Episteme 19 (2):247-263.
    According to John D. Norton's Material Theory of Induction, all reasonable inductive inferences are justified in virtue of background knowledge about local uniformities in nature. These local uniformities indicate that our samples are likely to be representative of our target population in our inductions. However, a variety of critics have noted that there are many circumstances in which induction seems to be reasonable, yet such background knowledge is apparently absent. I call such absences ‘the frontiers of science', where background scientific (...)
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  31. The Material Theory of Induction, by John Norton. [REVIEW]William Peden - 2022 - BJPS Review of Books.
    Even prior to its publication, John Norton’s book has stimulated debates about induction. Its publication will galvanize these discussions. Does it merit all this attention? Yes, and not just from philosophers of science. Practically all philosophers will find novel and thought-provoking ideas, with implications for their research.
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  32. Generalization Bias in Science.Uwe Peters, Alexander Krauss & Oliver Braganza - 2022 - Cognitive Science 46 (9):e13188.
    Many scientists routinely generalize from study samples to larger populations. It is commonly assumed that this cognitive process of scientific induction is a voluntary inference in which researchers assess the generalizability of their data and then draw conclusions accordingly. We challenge this view and argue for a novel account. The account describes scientific induction as involving by default a generalization bias that operates automatically and frequently leads researchers to unintentionally generalize their findings without sufficient evidence. The result is unwarranted, overgeneralized (...)
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  33. Peirce, Pedigree, Probability.Rush T. Stewart & Tom F. Sterkenburg - 2022 - Transactions of the Charles S. Peirce Society 58 (2):138-166.
    An aspect of Peirce’s thought that may still be underappreciated is his resistance to what Levi calls _pedigree epistemology_, to the idea that a central focus in epistemology should be the justification of current beliefs. Somewhat more widely appreciated is his rejection of the subjective view of probability. We argue that Peirce’s criticisms of subjectivism, to the extent they grant such a conception of probability is viable at all, revert back to pedigree epistemology. A thoroughgoing rejection of pedigree in the (...)
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  34. Designing Genetic Engineering Technologies For Human Values.Steven Umbrello - 2022 - Etica E Politica (2):481-510.
    Genetic engineering technologies are a subclass of the biotechnology family, and are concerned with the use of laboratory-based technologies to intervene with a given organism at the genetic level, i.e., the level of its DNA. This class of technologies could feasibly be used to treat diseases and disabilities, create disease-resistant crops, or even be used to enhance humans to make them more resistant to certain environmental conditions. However, both therapeutic and enhancement applications of genetic engineering raise serious ethical concerns. This (...)
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  35. On the gnoseologic principles of Bertrand Russell.Rafael Andrés Alemañ-Berenguer - 2021 - Naturaleza y Libertad. Revista de Estudios Interdisciplinares.
    Exposed in 1948, within his masterpiece on the scope and limits of human knowledge, the epistemological tenets that Bertrand Russell regarded as fundamental elements in the construction of scientific knowledge, are still worthy of a detailed discussion today. Given the excellence of the author, it will not be surprising to see that Russell's gnoseologic postulates, even for the present scientific view, address some of the most controversial questions still to be solved in the theory of knowledge.
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  36. Inductive metaphysics: Editors' introduction.Kristina Engelhard, Christian J. Feldbacher-Escamilla, Alexander Gebharter & Ansgar Seide - 2021 - Grazer Philosophische Studien 98 (1):1-26.
    This introduction consists of two parts. In the first part, the special issue editors introduce inductive metaphysics from a historical as well as from a systematic point of view and discuss what distinguishes it from other modern approaches to metaphysics. In the second part, they give a brief summary of the individual articles in this special issue.
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  37. "Objective Purport, Relational Confirmation, and the Presumption of Moral Objectivism: A Probabilistic Argument from Moral Experience".Tanner Hammond - 2021 - Southwest Philosophy Review 37 (1).
    All else being equal, can granting the objective purport of moral experience support a presumption in favor of some form of moral objectivism? Don Loeb (2007) has argued that even if we grant that moral experience appears to present us with a realm of objective moral fact—something he denies we have reason to do in the first place—the objective purport of moral experience cannot by itself provide even prima facie support for moral objectivism. In this paper, I contend against Loeb (...)
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  38. Modal inferences in science: a tale of two epistemologies.Ilmari Hirvonen, Rami Koskinen & Ilkka Pättiniemi - 2021 - Synthese 199 (5-6):13823-13843.
    Recent epistemology of modality has seen a growing trend towards metaphysics-first approaches. Contrastingly, this paper offers a more philosophically modest account of justifying modal claims, focusing on the practices of scientific modal inferences. Two ways of making such inferences are identified and analyzed: actualist-manipulationist modality and relative modality. In AM, what is observed to be or not to be the case in actuality or under manipulations, allows us to make modal inferences. AM-based inferences are fallible, but the same holds for (...)
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  39. Does the Dome Defeat the Material Theory of Induction?William Peden - 2021 - Erkenntnis 88 (5):2171-2190.
    According to John D. Norton's Material Theory of Induction, all inductive inferences are justified by local facts, rather than their formal features or some grand principles of nature's uniformity. Recently, Richard Dawid (Found Phys 45(9):1101–1109, 2015) has offered a challenge to this theory: in an adaptation of Norton's own celebrated "Dome" thought experiment, it seems that there are certain inductions that are intuitively reasonable, but which do not have any local facts that could serve to justify them in accordance with (...)
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  40. The no-free-lunch theorems of supervised learning.Tom F. Sterkenburg & Peter D. Grünwald - 2021 - Synthese 199 (3-4):9979-10015.
    The no-free-lunch theorems promote a skeptical conclusion that all possible machine learning algorithms equally lack justification. But how could this leave room for a learning theory, that shows that some algorithms are better than others? Drawing parallels to the philosophy of induction, we point out that the no-free-lunch results presuppose a conception of learning algorithms as purely data-driven. On this conception, every algorithm must have an inherent inductive bias, that wants justification. We argue that many standard learning algorithms should rather (...)
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  41. Privileged-Perspective Realism in the Quantum Multiverse.Nora Berenstain - 2020 - In David Glick, George Darby & Anna Marmodoro (eds.), The Foundation of Reality: Fundamentality, Space, and Time. Oxford: Oxford University Press.
    Privileged-perspective realism (PPR) is a version of metaphysical realism that takes certain irreducibly perspectival facts to be partly constitutive of reality. PPR asserts that there is a single metaphysically privileged standpoint from which these perspectival facts obtain. This chapter discusses several views that fall under the category of privileged-perspective realism. These include presentism, which is PPR about tensed facts, and non-multiverse interpretations of quantum mechanics, which the chapter argues, constitute PPR about world-indexed facts. Using the framework of the bird perspective (...)
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  42. On the Limits of Experimental Knowledge.Peter Evans & Karim P. Y. Thebault - 2020 - Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378 (2177).
    To demarcate the limits of experimental knowledge, we probe the limits of what might be called an experiment. By appeal to examples of scientific practice from astrophysics and analogue gravity, we demonstrate that the reliability of knowledge regarding certain phenomena gained from an experiment is not circumscribed by the manipulability or accessibility of the target phenomena. Rather, the limits of experimental knowledge are set by the extent to which strategies for what we call ‘inductive triangulation’ are available: that is, the (...)
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  43. The Multiplicity of Explanation in Cognitive Science.Raoul Gervais - 2020 - Foundations of Science 26 (4):1089–1104.
    In this paper, I argue that explaining cognitive behavior can be achieved through what I call hybrid explanatory inferences: inferences that posit mechanisms, but also draw on observed regularities. Moreover, these inferences can be used to achieve unification, in the sense developed by Allen Newel in his work on cognitive architectures. Thus, it seems that explanatory pluralism and unification do not rule out each other in cognitive science, but rather that the former represents a way to achieve the latter.
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  44. 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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  45. Law without law: From observer states to physics via algorithmic information theory.Markus P. Müller - 2020 - Quantum 4:301.
    According to our current conception of physics, any valid physical theory is supposed to describe the objective evolution of a unique external world. However, this condition is challenged by quantum theory, which suggests that physical systems should not always be understood as having objective properties which are simply revealed by measurement. Furthermore, as argued below, several other conceptual puzzles in the foundations of physics and related fields point to limitations of our current perspective and motivate the exploration of an alternative: (...)
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  46. Learning from Non-Causal Models.Francesco Nappo - 2020 - Erkenntnis 87 (5):2419-2439.
    This paper defends the thesis of learning from non-causal models: viz. that the study of some model can prompt justified changes in one’s confidence in empirical hypotheses about a real-world target in the absence of any known or predicted similarity between model and target with regards to their causal features. Recognizing that we can learn from non-causal models matters not only to our understanding of past scientific achievements, but also to contemporary debates in the philosophy of science. At one end (...)
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  47. Introduction to Formal Philosophy, edited by Sven Ove Hansson, Vincent F. Hendricks, Esther Michelsen Kjeldahl. [REVIEW]William Peden - 2020 - Teaching Philosophy 43 (2):215-218.
  48. A Validation of Knowledge: A New, Objective Theory of Axioms, Causality, Meaning, Propositions, Mathematics, and Induction.Ronald Pisaturo - 2020 - Norwalk, Connecticut: Prime Mover Press.
    This book seeks to offer original answers to all the major open questions in epistemology—as indicated by the book’s title. These questions and answers arise organically in the course of a validation of the entire corpus of human knowledge. The book explains how we know what we know, and how well we know it. The author presents a positive theory, motivated and directed at every step not by a need to reply to skeptics or subjectivists, but by the need of (...)
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  49. The Inductive Route Towards Necessity.Quentin Ruyant - 2020 - Acta Analytica 35 (2):147-163.
    It is generally assumed that relations of necessity cannot be known by induction on experience. In this paper, I propose a notion of situated possibilities, weaker than nomic possibilities, that is compatible with an inductivist epistemology for modalities. I show that assuming this notion, not only can relations of necessity be known by induction on our experience, but such relations cannot be any more underdetermined by experience than universal regularities. This means that any one believing in a universal regularity is (...)
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  50. The material theory of object-induction and the universal optimality of meta-induction: Two complementary accounts.Gerhard Schurz & Paul Thorn - 2020 - Studies in History and Philosophy of Science Part A 82:88-93.
1 — 50 / 485