Results for 'Mohran Bayed'

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  1. An Intelligent Tutoring System for Health Problems Related To Addiction of Video Game Playing.Mohran H. Al-Bayed & Samy S. Abu Naser - 2017 - International Journal of Advanced Scientific Research 2 (1):4-10.
    Lately in the past couple of years, there are an increasing in the normal rate of playing computer games or video games compared to the E-learning content that are introduced for the safety of our children, and the impact of the video game addictiveness that ranges from (Musculoskeletal issues, Vision problems and Obesity). Furthermore, this paper introduce an intelligent tutoring system for both parent and their children for enhancement the experience of gaming and tell us about the health problems and (...)
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  2. AI in Leadership: Transforming Decision-Making and Strategic Vision.Mohran H. Al-Bayed, Mohanad Hilles, Ibrahim Haddad, Marah M. Al-Masawabe, Mohammed Ibrahim Alhabbash, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Pedagogical Research (IJAPR) 8 (9):1-7.
    The integration of Artificial Intelligence (AI) into leadership practices is rapidly transforming organizational dynamics and decision-making processes. This paper explores the ways in which AI enhances leadership effectiveness by providing data- driven insights, optimizing decision-making, and automating routine tasks. Additionally, it examines the challenges leaders face when adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to offer a comprehensive (...)
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  3. Intelligent Plagiarism Detection for Electronic Documents.Mohran H. J. Al-Bayed - 2017 - Dissertation, Al-Azhar University, Gaza
    Plagiarism detection is the process of finding similarities on electronic based documents. Recently, this process is highly required because of the large number of available documents on the internet and the ability to copy and paste the text of relevant documents with simply Control+C and Control+V commands. The proposed solution is to investigate and develop an easy, fast, and multi-language support plagiarism detector with the easy of one click to detect the document plagiarism. This process will be done with the (...)
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  4. ITS for health problems related to addiction of video game playing.Mohran Bayed - 2017 - International Journal of Advanced Scientific Research 1 (2):4-10.
    Lately in the past couple of years, there are an increasing in the normal rate of playing computer games or video games compared to the E-learning content that are introduced for the safety of our children, and the impact of the video game addictiveness that ranges from (Musculoskeletal issues, Vision problems and Obesity). Furthermore, this paper introduce an intelligent tutoring system for both parent and their children for enhancement the experience of gaming and tell us about the health problems and (...)
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  5. Detecting Health Problems Related to Addiction of Video Game Playing Using an Expert System.Samy S. Abu Naser & Mohran H. Al-Bayed - 2016 - World Wide Journal of Multidisciplinary Research and Development 2 (9):7-12.
    Today’s everyone normal life can include a normal rate of playing computer games or video games; but what about an excessive or compulsive use of video games that impact on our life? Our kids, who usually spend a lot of time in playing video games will likely have a trouble in paying attention to their school lessons. In this paper, we introduce an expert system to help users in getting the correct diagnosis of the health problem of video game addictions (...)
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  6. Causal Bayes nets and token-causation: Closing the gap between token-level and type-level.Alexander Gebharter & Andreas Hüttemann - 2025 - Erkenntnis 90 (1):43-65.
    Causal Bayes nets (CBNs) provide one of the most powerful tools for modelling coarse-grained type-level causal structure. As in other fields (e.g., thermodynamics) the question arises how such coarse-grained characterisations are related to the characterisation of their underlying structure (in this case: token-level causal relations). Answering this question meets what is called a “coherence-requirement” in the reduction debate: How are different accounts of one and the same system (or kind of system) related to each other. We argue that CBNs as (...)
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  7. Bayes, predictive processing, and the cognitive architecture of motor control.Daniel C. Burnston - 2021 - Consciousness and Cognition 96 (C):103218.
    Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and predictive processing models of cognition for views of overall cognitive architecture. Many of these models are hierarchical ; they posit generative models at multiple distinct "levels," whose job is to predict the consequences of sensory input at lower levels. I articulate one possible position that could be implied by these models, namely, that there is a continuous hierarchy of perception, cognition, and action control comprising levels (...)
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  8. Bayes's theorem. [REVIEW]Massimo Pigliucci - 2005 - Quarterly Review of Biology 80 (1):93-95.
    About a British Academy collection of papers on Bayes' famous theorem.
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  9. Causal Direction in Causal Bayes Nets.Reuben Stern & Benjamin Eva - forthcoming - Philosophy of Science:1-11.
    Some authors maintain that we can use causal Bayes nets to infer whether X → Y or X ← Y by consulting a probability distribution defined over some exogenous source of variation for X or Y . We raise a problem for this approach. Specifically, we point out that there are cases where an exogenous cause of X (Ex) has no probabilistic influence on Y no matter the direction of causation — namely, cases where Ex → X → Y and (...)
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  10. Ang Ma’i bilang Bay: Isang Muling Pagbasa at Pagtatasa.Jolan Saluria - 2024 - Dalumat: Multikultural at Multidisiplinaryong e-Journal Sa Araling Pilipino 9 (1):126-143.
    Ang papel na ito ay komentaryo sa artikulong—Ma'I in Chinese Records—Mindoro or Bai? An Examination of a Historical Puzzle ni Go Bon Juan. Layunin ng pag-aaral na ito na lumikha ng isang mapanglagom at preliminaryong pagbasa sa Ma’i bilang isang suliraning historiograpikal. Sa muling pagbasang ito ay pagtutuunan ng pansin ang maikling pagbaybay sa historiograpiya nito na susundan naman ng interogasyon at pagbibigay kritik sa kamakailang pag-aaral dito ni Go Bon Juan at mga suliraning kinakaharap ng kaniyang interpretasyon na umiinog (...)
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  11. Nature, Science, Bayes 'Theorem, and the Whole of Reality‖.Moorad Alexanian - manuscript
    A fundamental problem in science is how to make logical inferences from scientific data. Mere data does not suffice since additional information is necessary to select a domain of models or hypotheses and thus determine the likelihood of each model or hypothesis. Thomas Bayes’ Theorem relates the data and prior information to posterior probabilities associated with differing models or hypotheses and thus is useful in identifying the roles played by the known data and the assumed prior information when making inferences. (...)
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  12. 'Beyond that which the victim suffers in death alone': Pain, Orientalism, and Non-violence at Guantanamo Bay.John Harfouch - forthcoming - Brill.
    Abstract: I argue that Orientalism continues to construct Arabs as subjects that cannot suffer violence, particularly the violence of torture. Beginning with Edward Said’s observation that Orientalists constructed ‘Arabs’ in the nineteenth -century as inorganic, metallic, and mineralized beings, I trace these themes through various sites in and around Guantanamo Bay. One finds the tropes of Orientalism in the Bybee memo as well as in the diary of Mohamedou Ould Slahi. Through these three distinct but related moments, one finds that (...)
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  13. Assessing theories, Bayes style.Franz Huber - 2008 - Synthese 161 (1):89-118.
    The problem addressed in this paper is “the main epistemic problem concerning science”, viz. “the explication of how we compare and evaluate theories [...] in the light of the available evidence” (van Fraassen, BC, 1983, Theory comparison and relevant Evidence. In J. Earman (Ed.), Testing scientific theories (pp. 27–42). Minneapolis: University of Minnesota Press). Sections 1– 3 contain the general plausibility-informativeness theory of theory assessment. In a nutshell, the message is (1) that there are two values a theory should exhibit: (...)
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  14. Gettier as Generalization Failure: A PAC–Bayes Approach to Anti-Luck.Lorand Bruhacs - manuscript
    Gettier cases suggest that justified true belief can fail through luck: a belief may fit available evidence while failing to track truth across relevant alternatives. We formalize a central class of these failures as epistemic overfitting: evidential success without robust truth-tracking under a modeled evidence-generating structure. Technically, we develop an algorithmic PAC--Bayes framework over posteriors, so complexity penalizes the full belief state rather than only a single hypothesis. The result is a finite-sample anti-luck certificate that links evidential fit, posterior complexity, (...)
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  15. Application of Naive Bayes Model, SVM and Deep Learning Predicting.Martono Aris, Padeli Padeli & Sudaryono Sudaryono - 2023 - Cices (Cyberpreneurship Innovative and Creative Exact and Social Science) 9 (1):93-101.
    The college hopes that every semester students are able to pay tuition properly and smoothly. The hope is that the institution will be able to maintain monthly cash flow so that its operational and maintenance costs can be met. Therefore, this study was conducted to predict and fulfill the institution's cash-in from the method of paying tuition fees either by cash, installments, or sometimes late payments every semester. In predicting the method of paying tuition fees, using student profile data (name, (...)
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  16. Belief revision generalized: a joint characterization of Bayes's and Jeffrey's rules.Franz Dietrich, Christian List & Richard Bradley - 2015 - Journal of Economic Theory 162:352-371.
    We present a general framework for representing belief-revision rules and use it to characterize Bayes's rule as a classical example and Jeffrey's rule as a non-classical one. In Jeffrey's rule, the input to a belief revision is not simply the information that some event has occurred, as in Bayes's rule, but a new assignment of probabilities to some events. Despite their differences, Bayes's and Jeffrey's rules can be characterized in terms of the same axioms: responsiveness, which requires that revised beliefs (...)
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  17. Comparative Analysis of Deep Learning and Naïve Bayes for Language Processing Task.Olalere Abiodun - forthcoming - International Journal of Research and Innovation in Applied Sciences.
    Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with least performance of (...)
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  18. Report on "Bayes By the Sea".William Peden - 2019 - The Reasoner 13 (10):3-4.
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  19. John Earman's 'bayes or bust? A critical examination of bayesian confirmation theory' (book review). [REVIEW]David Christensen - 1994 - Philosophical Review 103 (2):345-347.
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  20. Do Bayesian Models of Cognition Show That We Are (Bayes) Rational?Arnon Levy - forthcoming - Philosophy of Science:1-13.
    According to [Bayesian] models” in cognitive neuroscience, says a recent textbook, “the human mind behaves like a capable data scientist”. Do they? That is to say, do such model show we are rational? I argue that Bayesian models of cognition, perhaps surprisingly, do not and indeed cannot, show that we are Bayesian-rational. The key reason is that such models appeal to approximations, a fact that carries significant implications. After outlining the argument, I critique two responses, seen in recent cognitive neuroscience. (...)
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  21. Implementation and Comparison of Deep Learning with Naïve Bayes for Language Processing (4th edition).Abiodun Olalere - 2024 - Internation Journal of Research and Innovation in Appliad Science:1-6.
    Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with least performance of (...)
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  22. An investigation into the performances of the Current state-of-the-art Naive Bayes, Non-Bayesian and Deep Learning Based Classifier for Phishing Detection: A Survey. [REVIEW]Tosin Ige - manuscript
    Phishing is one of the most effective ways in which cybercriminals get sensitive details such as credentials for online banking, digital wallets, state secrets, and many more from potential victims. They do this by spamming users with malicious URLs with the sole purpose of tricking them into divulging sensitive information which is later used for various cybercrimes. In this research, we did a comprehensive review of current state-of-the-art machine learning and deep learning phishing detection techniques to expose their vulnerabilities and (...)
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  23. A dual approach to Bayesian inference and adaptive control.Leigh Tesfatsion - 1982 - Theory and Decision 14 (2):177-194.
    Probability updating via Bayes' rule often entails extensive informational and computational requirements. In consequence, relatively few practical applications of Bayesian adaptive control techniques have been attempted. This paper discusses an alternative approach to adaptive control, Bayesian in spirit, which shifts attention from the updating of probability distributions via transitional probability assessments to the direct updating of the criterion function, itself, via transitional utility assessments. Results are illustrated in terms of an adaptive reinvestment two-armed bandit problem.
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  24. Deduction, Induction and the Art of Clinical Reasoning in Medical Education: Systematic Review and Bayesian Proposal.Marcos Sousa & Túlio Aguiar - 2022 - Arq Bras Cardiol 119 (5 suppl):27-34.
    Background: Clinical reasoning is at the core of medical practice and entangled in a conceptual confusion. The duality theory in probability allows to evaluate its objective and subjective aspects. -/- Objectives: To conduct a systematic review of the literature about clinical reasoning in decision making in medical education and to propose a "reasoning based on the Bayesian rule" (RBBR). -/- Methods: A systematic review on PubMed was conducted (until February 27, 2022), following a strict methodology, by a researcher experienced in (...)
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  25. Why do we need to employ Bayesian statistics and how can we employ it in studies of moral education?: With practical guidelines to use JASP for educators and researchers.Hyemin Han - 2018 - Journal of Moral Education 47 (4):519-537.
    ABSTRACTIn this article, we discuss the benefits of Bayesian statistics and how to utilize them in studies of moral education. To demonstrate concrete examples of the applications of Bayesian statistics to studies of moral education, we reanalyzed two data sets previously collected: one small data set collected from a moral educational intervention experiment, and one big data set from a large-scale Defining Issues Test-2 survey. The results suggest that Bayesian analysis of data sets collected from moral educational studies can provide (...)
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  26. Support for Geometric Pooling.Jean Baccelli & Rush T. Stewart - 2023 - Review of Symbolic Logic 16 (1):298-337.
    Supra-Bayesianism is the Bayesian response to learning the opinions of others. Probability pooling constitutes an alternative response. One natural question is whether there are cases where probability pooling gives the supra-Bayesian result. This has been called the problem of Bayes-compatibility for pooling functions. It is known that in a common prior setting, under standard assumptions, linear pooling cannot be nontrivially Bayes-compatible. We show by contrast that geometric pooling can be nontrivially Bayes-compatible. Indeed, we show that, under certain assumptions, geometric and (...)
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  27. Performance Comparison and Implementation of Bayesian Variants for Network Intrusion Detection.Tosin Ige & Christopher Kiekintveld - 2023 - Proceedings of the IEEE 1:5.
    Bayesian classifiers perform well when each of the features is completely independent of the other which is not always valid in real world applications. The aim of this study is to implement and compare the performances of each variant of the Bayesian classifier (Multinomial, Bernoulli, and Gaussian) on anomaly detection in network intrusion, and to investigate whether there is any association between each variant’s assumption and their performance. Our investigation showed that each variant of the Bayesian algorithm blindly follows its (...)
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  28. Modelling competing legal arguments using Bayesian model comparison and averaging.Martin Neil, Norman Fenton, David Lagnado & Richard David Gill - 2019 - Artificial Intelligence and Law 27 (4):403-430.
    Bayesian models of legal arguments generally aim to produce a single integrated model, combining each of the legal arguments under consideration. This combined approach implicitly assumes that variables and their relationships can be represented without any contradiction or misalignment, and in a way that makes sense with respect to the competing argument narratives. This paper describes a novel approach to compare and ‘average’ Bayesian models of legal arguments that have been built independently and with no attempt to make them consistent (...)
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  29. Spinoza et Hume sur le miracle et le témoignage : une perspective épistémologique.Jacques J. Rozenberg - 2025 - ThéoRèmes 22 (22).
    Résumé : Le Tractatus Theologico-Politicus (TTP) de Spinoza, paru en 1670, a ébranlé l’ensemble des valeurs judéo-chrétiennes, en sapant les fondements de toutes les particularités nationales et religieuses européennes. Il s’attaquait ainsi aux assises des croyances traditionnelles, en contestant notamment les notions de miracle et de prophétie. Même si l’auteur de l’Ethique ne se trouve mentionné que dans le Traité de la Nature Humaine, et que les philosophies de Spinoza et de Hume apparaissent parfois comme étant antithétiques, elles présentent toutefois (...)
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  30. Can a Significance Test Be Genuinely Bayesian?Julio Michael Stern, Carlos Alberto de Braganca Pereira & Sergio Wechsler - 2008 - Bayesian Analysis 3 (1):79-100.
    The Full Bayesian Significance Test, FBST, is extensively reviewed. Its test statistic, a genuine Bayesian measure of evidence, is discussed in detail. Its behavior in some problems of statistical inference like testing for independence in contingency tables is discussed.
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  31. Evidence and Credibility: Full Bayesian Significance Test for Precise Hypotheses.Julio Michael Stern & Carlos Alberto de Braganca Pereira - 1999 - Entropy 1 (1):69-80.
    A Bayesian measure of evidence for precise hypotheses is presented. The intention is to give a Bayesian alternative to significance tests or, equivalently, to p-values. In fact, a set is defined in the parameter space and the posterior probability, its credibility, is evaluated. This set is the “Highest Posterior Density Region” that is “tangent” to the set that defines the null hypothesis. Our measure of evidence is the complement of the credibility of the “tangent” region.
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  32. Causal Markov Violations and Hidden Mechanisms.Niels Skovgaard-Olsen - forthcoming - Journal of Experimental Psychology: Learning, Memory, and Cognition.
    Past studies have shown that while causal Bayes Nets account for many of the causal inferences participants make in psychological experiments, persistent violations of one of their most fundamental axioms, the causal Markov condition, are found. Previous studies have attempted to account for such violations by conjecturing that participants posit causal representations that diverge from the causal representations intended by the experimenters. In this paper, a novel method is presented for addressing the unsolved problem of how to determine which causal (...)
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  33. 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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  34. Secular Reincarnation: Existence, Evidence, and the Boundaries of Bayesian Reasoning.Luke R. Allen - manuscript
    Philosophers often appeal to Bayesian confirmation theory to render speculative metaphysical arguments more rigorous. But can a probabilistic framework designed for empirical data decide questions of metaphysics? This paper argues that Huemer’s Bayesian “existence → immortality” inference fails on two independent grounds. First, the comparison tacitly shifts the content of the evidence across the competing identity theories: treating “I exist now” as a different event under a restrictive view than under a permissive view. So, the Bayesian evidence is ill-defined. Second, (...)
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  35. On the evidence of testimony for miracles: A bayesian interpretation of David Hume's analysis.Jordan Howard Sobel - 1987 - Philosophical Quarterly 37 (147):166-186.
    A BAYESIAN ARTICULATION OF HUME’S VIEWS IS OFFERED BASED ON A FORM OF THE BAYES-LAPLACE THEOREM THAT IS SUPERFICIALLY LIKE A FORMULA OF CONDORCET’S. INFINITESIMAL PROBABILITIES ARE EMPLOYED FOR MIRACLES AGAINST WHICH THERE ARE ’PROOFS’ THAT ARE NOT OPPOSED BY ’PROOFS’. OBJECTIONS MADE BY RICHARD PRICE ARE DEALT WITH, AND RECENT EXPERIMENTS CONDUCTED BY AMOS TVERSKY AND DANIEL KAHNEMAN ARE CONSIDERED IN WHICH PERSONS TEND TO DISCOUNT PRIOR IMPROBABILITIES WHEN ASSESSING REPORTS OF WITNESSES.
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  36. Why adoption of causal modeling methods requires some metaphysics.Holly Andersen - 2024 - In Federica Russo & Phyllis Illari, The Routledge handbook of causality and causal methods. New York, NY: Routledge.
    I highlight a metaphysical concern that stands in the way of more widespread adoption of causal modeling techniques such as causal Bayes nets. Researchers in some fields may resist adoption due to concerns that they don't 'really' understand what they are saying about a system when they apply such techniques. Students in these fields are repeated exhorted to be cautious about application of statistical techniques to their data without a clear understanding of the conditions required for those techniques to yield (...)
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  37. (1 other version)Bayesian belief protection: A study of belief in conspiracy theories.Nina Poth & Krzysztof Dolega - 2022 - Philosophical Psychology.
    Several philosophers and psychologists have characterized belief in conspiracy theories as a product of irrational reasoning. Proponents of conspiracy theories apparently resist revising their beliefs given disconfirming evidence and tend to believe in more than one conspiracy, even when the relevant beliefs are mutually inconsistent. In this paper, we bring leading views on conspiracy theoretic beliefs closer together by exploring their rationality under a probabilistic framework. We question the claim that the irrationality of conspiracy theoretic beliefs stems from an inadequate (...)
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  38. Constructive Verification, Empirical Induction, and Falibilist Deduction: A Threefold Contrast.Julio Michael Stern - 2011 - Information 2 (4):635-650.
    This article explores some open questions related to the problem of verification of theories in the context of empirical sciences by contrasting three epistemological frameworks. Each of these epistemological frameworks is based on a corresponding central metaphor, namely: (a) Neo-empiricism and the gambling metaphor; (b) Popperian falsificationism and the scientific tribunal metaphor; (c) Cognitive constructivism and the object as eigen-solution metaphor. Each of one of these epistemological frameworks has also historically co-evolved with a certain statistical theory and method for testing (...)
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  39. The Metamathematics of Putnam’s Model-Theoretic Arguments.Tim Button - 2011 - Erkenntnis 74 (3):321-349.
    Putnam famously attempted to use model theory to draw metaphysical conclusions. His Skolemisation argument sought to show metaphysical realists that their favourite theories have countable models. His permutation argument sought to show that they have permuted models. His constructivisation argument sought to show that any empirical evidence is compatible with the Axiom of Constructibility. Here, I examine the metamathematics of all three model-theoretic arguments, and I argue against Bays (2001, 2007) that Putnam is largely immune to metamathematical challenges.
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  40. Running Causation Aground.Holly Andersen - 2023 - The Monist 106 (3):255-269.
    The reduction of grounding to causation, or each to a more general relation of which they are species, has sometimes been justified by the impressive inferential capacity of structural equation modelling, causal Bayes nets, and interventionist causal modelling. Many criticisms of this assimilation focus on how causation is inadequate for grounding. Here, I examine the other direction: how treating grounding in the image of causation makes the resulting view worse for causation. The distinctive features of causal modelling that make this (...)
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  41. Mad Speculation and Absolute Inhumanism: Lovecraft, Ligotti, and the Weirding of Philosophy.Ben Woodard - 2011 - Continent 1 (1):3-13.
    continent. 1.1 : 3-13. / 0/ – Introduction I want to propose, as a trajectory into the philosophically weird, an absurd theoretical claim and pursue it, or perhaps more accurately, construct it as I point to it, collecting the ground work behind me like the Perpetual Train from China Mieville's Iron Council which puts down track as it moves reclaiming it along the way. The strange trajectory is the following: Kant's critical philosophy and much of continental philosophy which has followed, (...)
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  42. Special Issue on Global Justice and Education.Julian Culp (ed.) - 2020
    When asking fundamental questions about education, philosophers have not shied away from giving radical answers. Jean-Jacques Rousseau, for example, who found himself disenchanted with the artificiality and pride that he encountered in 18th century Paris, advocated a laissez faire education in the countryside. Such an “education by nature,” Rousseau thought, would keep children at bay from morally corrupt society and would allow them to become authentic and sincere persons. Similarly concerned with moral education, in the early 20th century the American (...)
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  43. The Logic of Counterfactuals and the Epistemology of Causal Inference.Hanti Lin - manuscript
    The 2021 Nobel Prize in Economics recognized an epistemology of causal inference based on the Rubin causal model (Rubin 1974), which merits broader attention in philosophy. This model, in fact, presupposes a logical principle of counterfactuals, Conditional Excluded Middle (CEM), the locus of a pivotal debate between Stalnaker (1968) and Lewis (1973) on the semantics of counterfactuals. Proponents of CEM should recognize that this connection points to a new argument for CEM---a Quine-Putnam indispensability argument grounded in the Nobel-winning applications of (...)
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  44. Handlungstheoretisch erklärende Interpretationen als Mittel der semantischen Bedeutungsanalyse.Christoph Lumer - 1992 - In Lutz Danneberg & Friedrich Vollhardt, Vom Umgang mit Literatur und Literaturgeschichte. Metzler. pp. 75-113.
    ACTION-THEORETICALLY EXPLANATORY INTERPRETATIONS AS A MEANS OF SEMANTIC MEANING ANALYSIS The article first develops a general procedure for semantic meaning analysis in difficult cases where the meaning is very uncertain. The procedure consists of searching for one or more possible hypothetical causal explanations of the text, these explanations containing, among other things, the semantic intention of the author, his subjective reasons for this meaning and for the writing down of the text, but also the path of transmission of the text (...)
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  45. Low attention impairs optimal incorporation of prior knowledge in perceptual decisions.Jorge Morales, Guillermo Solovey, Brian Maniscalco, Dobromir Rahnev, Floris P. de Lange & Hakwan Lau - 2015 - Attention, Perception, and Psychophysics 77 (6):2021-2036.
    When visual attention is directed away from a stimulus, neural processing is weak and strength and precision of sensory data decreases. From a computational perspective, in such situations observers should give more weight to prior expectations in order to behave optimally during a discrimination task. Here we test a signal detection theoretic model that counter-intuitively predicts subjects will do just the opposite in a discrimination task with two stimuli, one attended and one unattended: when subjects are probed to discriminate the (...)
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  46. Bread prices and sea levels: why probabilistic causal models need to be monotonic.Vera Hoffmann-Kolss - 2024 - Philosophical Studies (9):1-16.
    A key challenge for probabilistic causal models is to distinguish non-causal probabilistic dependencies from true causal relations. To accomplish this task, causal models are usually required to satisfy several constraints. Two prominent constraints are the causal Markov condition and the faithfulness condition. However, other constraints are also needed. One of these additional constraints is the causal sufficiency condition, which states that models must not omit any direct common causes of the variables they contain. In this paper, I argue that the (...)
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  47. Mechanizmy predykcyjne i ich normatywność [Predictive mechanisms and their normativity].Michał Piekarski - 2020 - Warszawa, Polska: Liberi Libri.
    The aim of this study is to justify the belief that there are biological normative mechanisms that fulfill non-trivial causal roles in the explanations (as formulated by researchers) of actions and behaviors present in specific systems. One example of such mechanisms is the predictive mechanisms described and explained by predictive processing (hereinafter PP), which (1) guide actions and (2) shape causal transitions between states that have specific content and fulfillment conditions (e.g. mental states). Therefore, I am guided by a specific (...)
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  48. From Prediction to Coherence_ A Deterministic Substrate for Intelligence Beyond Probability.Devin Bostick - manuscript
    The Evolution Toward Coherence: How CODES Completes the Substrate -/- For more than two centuries, science and computation have treated probability and entropy as foundational — from Bayes to Boltzmann to Shannon. Yet each of these frameworks presupposed uncertainty as ontology rather than as a measurement artifact of incomplete phase detection. The CODES framework (Chirality of Dynamic Emergent Systems) redefines this foundation by introducing coherence as the lawful invariant of all emergent systems. -/- At its computational embodiment, the Resonance Intelligence (...)
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  49. The competition for knowledge: Shades of gray and rules of thumb.Luis M. Augusto - 2022 - Journal of Knowledge Structures and Systems 3 (3):50-62.
    All research is immersed in the competition for knowledge, but this is not always governed by fairness. In this opinion article, I elaborate on indicators of unfairness to be found in both evaluation guides and evaluation panels, and I spontaneously offer a number of rules of thumb meant to keep it at bay. Although they are explicitly offered to the Portuguese Foundation for Science and Technology (FCT) and in particular to the evaluation panel for Philosophy, Ethics and Religion of FCT's (...)
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  50. Measuring Complexity: Things That Go Wrong and How to Get It Right—Version 2.Vincent Vesterby - manuscript
    Seven problems that occur in attempts to measure complexity are pointed out as they occur in four proposed measurement techniques. Each example method is an improvement over the previous examples. It turns out, however, that none are up to the challenge of complexity. Apparently, there is no currently available method that truly gets the measure of complexity. There are two reasons. First, the most natural approach, quantitative analysis, is rendered inadequate by the very nature of complexity. Second, the intrinsic magnitude (...)
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