This category needs an editor. We encourage you to help if you are qualified.
Volunteer, or read more about what this involves.
Related categories
Subcategories:
198 found
Search inside:
(import / add options)   Order:
1 — 50 / 198
Material to categorize
  1. A. R. A. (1957). Probability in Logic. Review of Metaphysics 11 (2):348-348.
  2. R. A. A. (1957). Probability in Logic. [REVIEW] Review of Metaphysics 11 (2):348-348.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  3. Ken Akiba (2000). Shogenji's Probabilistic Measure of Coherence is Incoherent. Analysis 60 (4):356–359.
    Remove from this list   Direct download (9 more)  
     
    Export citation  
     
    My bibliography   26 citations  
  4. Staffan Angere (2008). Coherence as a Heuristic. Mind 117 (465):1-26.
    The impossibility results of Bovens and Hartmann (2003) and Olsson (2005) call into question the strength of the connection between coherence and truth. As part of the inquiry into this alleged link, I define a notion of degree of truth-conduciveness, relevant for measuring the usefulness of coherence measures as rules-of-thumb for assigning probabilities in situations of partial knowledge. I use the concept to compare the viability of some of the measures of coherence that have been suggested so far under different (...)
    Remove from this list   Direct download (6 more)  
     
    Export citation  
     
    My bibliography   13 citations  
  5. Staffan Angere (2007). The Defeasible Nature of Coherentist Justification. Synthese 157 (3):321 - 335.
    The impossibility results of Bovens and Hartmann (2003, Bayesian epistemology. Oxford: Clarendon Press) and Olsson (2005, Against coherence: Truth, probability and justification. Oxford: Oxford University Press.) show that the link between coherence and probability is not as strong as some have supposed. This paper is an attempt to bring out a way in which coherence reasoning nevertheless can be justified, based on the idea that, even if it does not provide an infallible guide to probability, it can give us an (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    My bibliography   7 citations  
  6. N. D. B. (1961). Markov Learning Models for Multiperson Interactions. Review of Metaphysics 15 (1):196-196.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  7. Patricia Baillie (1971). Confirmation and Probability: A Reply to Settle. British Journal for the Philosophy of Science 22 (3):285-286.
    Remove from this list   Direct download (8 more)  
     
    Export citation  
     
    My bibliography  
  8. Jonathan Baron (1987). Second-Order Probabilities and Belief Functions. Theory and Decision 23 (1):25-36.
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography   5 citations  
  9. M. S. Bartlett (1949). Probability in Logic, Mathematics and Science. Dialectica 3 (1‐2):104-113.
    Historically the emergence of a precise technical meaning for probability, as distinct from its vague popular useage, has taken time; and confusion still arises from the concept of probability having different meanings in different flelds of discourse. Its technical meaning and appropriate rules are surveyed in the flelds of logic , mathematics , and science , and the relation between these three aspects of probability theory discussed. ‐. M. S. B.
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography  
  10. Marianne Belis (2007). The Causal Roots of Probability. In Federica Russo & Jon Williamson (eds.), Causality and Probability in the Sciences. 5--295.
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  11. Gerry Curtis Bridgeman (2001). Practical Reasoning Through Coherent Goal Specification. Dissertation, Vanderbilt University
    In this work, I try to further specify what practical coherence should amount to. Any account of practical reasoning ought to be able to say something about how we ought to go about specifying our goals. One possibility is coherence theory. But coherence theory as it is normally conceived cannot be sufficient for rationality. Practical reasoning, which takes place over time, poses special difficulties for the coherence theorist. There is a danger that unless coherence theory has some element of stability (...)
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  12. Peter Brugger & Kirsten I. Taylor (2003). ESP: Extrasensory Perception or Effect of Subjective Probability? Journal of Consciousness Studies 10 (6-7):6-7.
    This paper consists of two parts. In the first, we discuss the neuropsychological correlates of belief in a 'paranormal' or magical causation of coincidences. In particular, we review experimental evidence demonstrating that believers in ESP and kindred forms of paranormal phenomena differ from disbelievers with respect to indices of sequential response production and semantic-associative processing. Not only do believers judge artificial coincidences as more 'meaningful' than disbelievers, they also more strongly suppress coincidental productions (i.e. repetitions) in their generation of random (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography   1 citation  
  13. E. Brunswik (1939). Probability as a Determiner of Rat Behavior. Journal of Experimental Psychology 25 (2):175.
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography   29 citations  
  14. B. C. (1982). Philosophical Problems of Statistical Inference. Review of Metaphysics 35 (4):907-909.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  15. Andrea Capotorti, Giulianella Coletti & Barbara Vantaggi (2008). Preferences Representable by a Lower Expectation: Some Characterizations. [REVIEW] Theory and Decision 64 (2-3):119-146.
    We propose two different characterizations for preference relations representable by lower (upper) expectations with the aim of removing either fair price or completeness requirements. Moreover, we give an explicit characterization for comparative degrees of belief on a finite algebra of events representable by lower probabilities.
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography  
  16. Bruno De Finetti (2008). Philosophical Lectures on Probability. Collected, Edited and Annotated by Alberto Mura. Springer.
    The book contains the transcription of a course on the foundations of probability given by the Italian mathematician Bruno de Finetti in 1979 at the a oeNational Institute of Advanced Mathematicsa in Rome.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography   2 citations  
  17. Lorenz Demey, Barteld Kooi & Joshua Sack (2014). Logic and Probability. In Edward N. Zalta (ed.), The Stanford Encyclopedia of Philosophy.
    Remove from this list  
     
    Export citation  
     
    My bibliography   2 citations  
  18. Mary Deutsch-McLeish (1991). A Study of Probabilities and Belief Functions Under Conflicting Evidence: Comparisons and New Methods. In B. Bouchon-Meunier, R. R. Yager & L. A. Zadeh (eds.), Uncertainty in Knowledge Bases. Springer 41--49.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  19. Igor Douven (2005). Basic Beliefs, Coherence, and Bootstrap Confirmation. In Rene van Woudenberg, Sabine Roeser & Ron Rood (eds.), Basic Belief and Basic Knowledge. Ontos-Verlag 4--57.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  20. Fred Dretske (1989). The Likelihood of Knowledge. Review of Metaphysics 42 (3):632-633.
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography  
  21. Kenny Easwaran (2014). Probability and Logic. Philosophy Compass 9 (12):876-883.
    Probability and logic are two branches of mathematics that have important philosophical applications. This article discusses several areas of intersection between them. Several involve the role for probability in giving semantics for logic or the role of logic in governing assignments of probability. Some involve probability over non-classical logic or self-referential sentences.
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    My bibliography  
  22. Leif Eriksen (1989). Confirmation, Paradox, and Logic. Philosophy of Science 56 (4):681-687.
    Paul Horwich has formulated a paradox which he believes to be even more virulent than the related Hempel paradox. I show that Horwich's paradox, as orginally formulated, has a purely logical solution, hence that it has no bearing on the theory of confirmation. On the other hand, it illuminates some undesirable traits of classical predicate logic. A revised formulation of the paradox is then dealt with in a way that implies a modest revision of Nicod's criterion.
    Remove from this list   Direct download (6 more)  
     
    Export citation  
     
    My bibliography  
  23. Branden Fitelson, Dempster-Shafer Functions as Metalinguistic Probability Functions.
    Let Ln be a sentential language with n atomic sentences {A1, . . . , An}. Let Sn = {s1, . . . , s2n} be the set of 2n state descriptions of Ln, in the following, canonical lexicographical truth-table order: State Description A1 A2 · · · An−1 An T T T T T s1 = A1 & A2 & · · · &An−1 & An T T T T F s1 = A1 & A2 & · · · (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography   1 citation  
  24. Branden Fitelson, Probabilistic Coherence From a Logical Point of View.
    – Foundation: Probabilistic Confirmation (c) from a Logical POV ∗ cph, eq as a “relevant” quantitative generalization of pe  hq ∗ cph, eq, so understood, is not Prpe  hq or Prph | eq, etc. ∗ cph, eq is something akin (ordinally) to the likelihood ratio..
    Remove from this list  
    Translate
      Direct download  
     
    Export citation  
     
    My bibliography   3 citations  
  25. Branden Fitelson (2003). A Probabilistic Theory of Coherence. Analysis 63 (3):194–199.
    Let E be a set of n propositions E1, ..., En. We seek a probabilistic measure C(E) of the ‘degree of coherence’ of E. Intuitively, we want C to be a quantitative, probabilistic generalization of the (deductive) logical coherence of E. So, in particular, we require C to satisfy the following..
    Remove from this list   Direct download (9 more)  
     
    Export citation  
     
    My bibliography   58 citations  
  26. Malcolm Forster, Chapter 3: Simplicity and Unification in Model Selection.
    This chapter examines four solutions to the problem of many models, and finds some fault or limitation with all of them except the last. The first is the naïve empiricist view that best model is the one that best fits the data. The second is based on Popper’s falsificationism. The third approach is to compare models on the basis of some kind of trade off between fit and simplicity. The fourth is the most powerful: Cross validation testing.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography   1 citation  
  27. Malcolm R. Forster (1995). The Golfer's Dilemma: A Reply to Kukla on Curve-Fitting. British Journal for the Philosophy of Science 46 (3):348-360.
    Curve-fitting typically works by trading off goodness-of-fit with simplicity, where simplicity is measured by the number of adjustable parameters. However, such methods cannot be applied in an unrestricted way. I discuss one such correction, and explain why the exception arises. The same kind of probabilistic explanation offers a surprising resolution to a common-sense dilemma.
    Remove from this list   Direct download (8 more)  
     
    Export citation  
     
    My bibliography   2 citations  
  28. Patrizio Frederic, Mario Di Bacco & Frank Lad (2012). Combining Expert Probabilities Using the Product of Odds. Theory and Decision 73 (4):605-619.
    We resolve a useful formulation of the question how a statistician can coherently incorporate the information in a consulted expert’s probability assessment for an event into a personal posterior probability assertion. Using a framework that recognises the total information available as composed of units available only to each of them along with units available to both, we show: that a sufficient statistic for all the information available to both the expert and the statistician is the product of their odds ratios (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography  
  29. Maria Carla Galavotti, Roberto Scazzieri & Patrick Suppes (eds.) (2008). Reasoning, Rationality and Probability. Center for the Study of Language and Inf.
    This volume broadens our concept of reasoning and rationality to allow for a more pluralistic and situational view of human thinking as a practical activity. Drawing on contributors across disciplines including philosophy, economics, psychology, statistics, computer science, engineering, and physics, _Reasoning, Rationality, and Probability_ argues that the search for strong theories should leave room for the construction of context-sensitive conceptual tools. Both science and everyday life, the authors argue, are too complex and multifaceted to be forced into ready-made schemata.
    Remove from this list  
     
    Export citation  
     
    My bibliography   2 citations  
  30. Richard T. De George (1990). Ethics and Coherence. Proceedings and Addresses of the American Philosophical Association 64 (3):39 - 52.
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    My bibliography   2 citations  
  31. Gianluca Giorgolo, Shalom Lappin & Alexander Clark, Towards a Statistical Model of Grammaticality.
    The question of whether it is possible to characterise grammatical knowledge in probabilistic terms is central to determining the relationship of linguistic representation to other cognitive domains. We present a statistical model of grammaticality which maps the probabilities of a statistical model for sentences in parts of the British National Corpus (BNC) into grammaticality scores, using various functions of the parameters of the model. We test this approach with a classifier on test sets containing different levels of syntactic infelicity. With (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  32. David H. Glass (2012). Inference to the Best Explanation: Does It Track Truth? Synthese 185 (3):411-427.
    In the form of inference known as inference to the best explanation there are various ways to characterise what is meant by the best explanation. This paper considers a number of such characterisations including several based on confirmation measures and several based on coherence measures. The goal is to find a measure which adequately captures what is meant by 'best' and which also yields the truth with a high degree of probability. Computer simulations are used to show that the overlap (...)
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    My bibliography   3 citations  
  33. Clark Glymour (2009). Causation and Statistical Inference. In Helen Beebee, Christopher Hitchcock & Peter Menzies (eds.), The Oxford Handbook of Causation. OUP Oxford
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  34. Matthew Harrison-Trainor, Wesley H. Holliday & Thomas F. Icard (2016). A Note on Cancellation Axioms for Comparative Probability. Theory and Decision 80 (1):159-166.
    We prove that the generalized cancellation axiom for incomplete comparative probability relations introduced by Rios Insua and Alon and Lehrer is stronger than the standard cancellation axiom for complete comparative probability relations introduced by Scott, relative to their other axioms for comparative probability in both the finite and infinite cases. This result has been suggested but not proved in the previous literature.
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography  
  35. Douglas N. Hoover (1978). Probability Logic. Annals of Mathematical Logic 14 (3):287-313.
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    My bibliography   13 citations  
  36. Kevin D. Hoover (2015). The Ontological Status of Shocks and Trends in Macroeconomics. Synthese 192 (11):3509-3532.
    Modern empirical macroeconomic models, known as structural autoregressions (SVARs) are dynamic models that typically claim to represent a causal order among contemporaneously valued variables and to merely represent non-structural (reduced-form) co-occurence between lagged variables and contemporaneous variables. The strategy is held to meet the minimal requirements for identifying the residual errors in particular equations in the model with independent, though otherwise not directly observable, exogenous causes (“shocks”) that ultimately account for change in the model. In nonstationary models, such shocks accumulate (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    My bibliography   1 citation  
  37. Kevin D. Hoover (2012). Causal Structure and Hierarchies of Models. Studies in History and Philosophy of Science Part C 43 (4):778-786.
    Economics prefers complete explanations: general over partial equilibrium, microfoundational over aggregate. Similarly, probabilistic accounts of causation frequently prefer greater detail to less as in typical resolutions of Simpson’s paradox. Strategies of causal refinement equally aim to distinguish direct from indirect causes. Yet, there are countervailing practices in economics. Representative-agent models aim to capture economic motivation but not to reduce the level of aggregation. Small structural vector-autoregression and dynamic stochastic general-equilibrium models are practically preferred to larger ones. The distinction between exogenous (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    My bibliography  
  38. Richard C. Jeffrey (1969). Statistical Explanation Vs. Statistical Inference. In Nicholas Rescher (ed.), Essays in Honor of Carl G. Hempel. Reidel 104--113.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography   11 citations  
  39. L. John (2002). Causal Probability. Synthese 132 (1-2):1-2.
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  40. Mark Kaplan (2008). Confidence and Probability. In Duncan Pritchard & Ram Neta (eds.), Arguing About Knowledge. Routledge 127.
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  41. Michael Harry Kelley (1969). Methodological Problems of Logical Probability. Dissertation, The University of Wisconsin - Madison
    Remove from this list  
     
    Export citation  
     
    My bibliography  
  42. Robert Kennes & Philippe Smets (1991). Fast Algorithms for Dempster-Shafer Theory. In B. Bouchon-Meunier, R. R. Yager & L. A. Zadeh (eds.), Uncertainty in Knowledge Bases. Springer 14--23.
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
  43. I. A. Kieseppä (1997). Akaike Information Criterion, Curve-Fitting, and the Philosophical Problem of Simplicity. British Journal for the Philosophy of Science 48 (1):21-48.
    The philosophical significance of the procedure of applying Akaike Information Criterion (AIC) to curve-fitting problems is evaluated. The theoretical justification for using AIC (the so-called Akaike's theorem) is presented in a rigorous way, and its range of validity is assessed by presenting both instances in which it is valid and counter-examples in which it is invalid. The philosophical relevance of the justification that this result gives for making one particular choice between simple and complicated hypotheses is emphasized. In addition, recent (...)
    Remove from this list   Direct download (7 more)  
     
    Export citation  
     
    My bibliography   2 citations  
  44. T. A. F. Kuipers (1971). Inductive Probability and the Paradox of Ideal Confirmation. Philosophica 17 (1):197-205.
  45. Łukasz Kukier, Marek Szydłowski & Paweł Tambor (2009). Kryterium Akaike: prostota w języku statystyki. Roczniki Filozoficzne 57 (1):91-126.
    Remove from this list  
    Translate
      Direct download  
     
    Export citation  
     
    My bibliography  
  46. André Kukla (1995). Forster and Sober on the Curve-Fitting Problem. British Journal for the Philosophy of Science 46 (2):248-252.
    Forster and Sober present a solution to the curve-fitting problem based on Akaike's Theorem. Their analysis shows that the curve with the best epistemic credentials need not always be the curve that most closely fits the data. However, their solution does not, without further argument, avoid the two difficulties that are traditionally associated with the curve-fitting problem: that there are infinitely many equally good candidate-curves relative to any given set of data, and that these best candidates include curves with indefinitely (...)
    Remove from this list   Direct download (9 more)  
     
    Export citation  
     
    My bibliography   3 citations  
  47. Henry E. Kyburg (1991). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference by Judea Pearl. Journal of Philosophy 88 (8):434-437.
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    My bibliography  
  48. Noël Laverny & Jérôme Lang (2005). From Knowledge-Based Programs to Graded Belief-Based Programs, Part I: On-Line Reasoning. Synthese 147 (2):277 - 321.
    Knowledge-based programs (KBPs) are a powerful notion for expressing action policies in which branching conditions refer to implicit knowledge and call for a deliberation task at execution time. However, branching conditions in KBPs cannot refer to possibly erroneous beliefs or to graded belief, such as “if my belief that φ holds is high then do some action α else perform some sensing action β”.
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    My bibliography  
  49. Keith Lehrer (1980). Coherence and the Racehorse Paradox. Midwest Studies in Philosophy 5 (1):183-192.
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    My bibliography   1 citation  
  50. Bert Leuridan (2007). Galton's Blinding Glasses. Modern Statistics Hiding Causal Structure in Early Theories of Inheritance. In Federica Russo & Jon Williamson (eds.), Causality and Probability in the Sciences. 243--262.
    ABSTRACT. Probability and statistics play an important role in contemporary -philosophy of causality. They are viewed as glasses through which we can see or detect causal relations. However, they may sometimes act as blinding glasses, as I will argue in this paper. In the 19th century, Francis Galton tried to statistically analyze hereditary phenomena. Although he was a far better statistician than Gregor Mendel, his biological theory turned out to be less fruitful. This was no sheer accident. His knowledge of (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    My bibliography  
1 — 50 / 198