100 found
Order:
Disambiguations
Daniel Osherson [57]Daniel N. Osherson [32]D. Osherson [7]D. N. Osherson [3]
DanielN Osherson [1]
  1. On the adequacy of prototype theory as a theory of concepts.Daniel N. Osherson & Edward E. Smith - 1981 - Cognition 9 (1):35-58.
  2.  50
    Category-based induction.Daniel N. Osherson, Edward E. Smith, Ormond Wilkie & Alejandro López - 1990 - Psychological Review 97 (2):185-200.
  3. Probabilistic coherence and proper scoring rules.Joel Predd, Robert Seiringer, Elliott Lieb, Daniel Osherson, H. Vincent Poor & Sanjeev Kulkarni - 2009 - IEEE Transactions on Information Theory 55 (10):4786-4792.
    We provide self-contained proof of a theorem relating probabilistic coherence of forecasts to their non-domination by rival forecasts with respect to any proper scoring rule. The theorem recapitulates insights achieved by other investigators, and clarifi es the connection of coherence and proper scoring rules to Bregman divergence.
    Direct download  
     
    Export citation  
     
    Bookmark   68 citations  
  4.  41
    Elements of Scientific Inquiry.Eric Martin & Daniel N. Osherson - 1998 - MIT Press.
    Eric Martin and Daniel N. Osherson present a theory of inductive logic built on model theory. Their aim is to extend the mathematics of Formal Learning Theory to a more general setting and to provide a more accurate image of empirical inquiry. The formal results of their study illuminate aspects of scientific inquiry that are not covered by the commonly applied Bayesian approach.
    Direct download  
     
    Export citation  
     
    Bookmark   31 citations  
  5.  74
    Combining Prototypes: A Selective Modification Model.Edward E. Smith, Daniel N. Osherson, Lance J. Rips & Margaret Keane - 1988 - Cognitive Science 12 (4):485-527.
    No categories
    Direct download  
     
    Export citation  
     
    Bookmark   61 citations  
  6.  74
    Comparison of confirmation measures.Katya Tentori, Vincenzo Crupi, Nicolao Bonini & Daniel Osherson - 2007 - Cognition 103 (1):107-119.
  7.  78
    The conjunction fallacy: a misunderstanding about conjunction?Daniel Osherson - 2004 - Cognitive Science 28 (3):467-477.
    It is easy to construct pairs of sentences X, Y that lead many people to ascribe higher probability to the conjunction X-and-Y than to the conjuncts X, Y. Whether an error is thereby committed depends on reasoners’ interpretation of the expressions “probability” and “and.” We report two experiments designed to clarify the normative status of typical responses to conjunction problems. © 2004 Cognitive Science Society, Inc. All rights reserved.
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   41 citations  
  8.  47
    Methods for distance-based judgment aggregation.M. K. Miller & D. Osherson - unknown
    Judgment aggregation theory, which concerns the translation of individual judgments on logical propositions into consistent group judgments, has shown that group consistency generally cannot be guaranteed if each proposition is treated independently from the others. Developing the right method of abandoning independence is thus a high-priority goal. However, little work has been done in this area outside of a few simple approaches. To fill the gap, we compare four methods based on distance metrics between judgment sets. The methods generalize the (...)
    Direct download  
     
    Export citation  
     
    Bookmark   23 citations  
  9.  59
    Gradedness and conceptual combination.Daniel N. Osherson & Edward E. Smith - 1982 - Cognition 12 (3):299-318.
  10.  46
    Task-specificity and species-specificity in the study of language: A methodological note.Daniel N. Osherson & Thomas Wasow - 1976 - Cognition 4 (2):203-214.
  11.  66
    Conceptual Combination with Prototype Concepts.Edward E. Smith & Daniel N. Osherson - 1984 - Cognitive Science 8 (4):337-361.
    No categories
    Direct download  
     
    Export citation  
     
    Bookmark   30 citations  
  12. Updating beliefs in light of uncertain evidence: Descriptive assessment of Jeffrey's rule.Daniel Osherson & Jiaying Zhao - 2010 - Thinking and Reasoning 16 (4):288-307.
    Jeffrey (1983) proposed a generalization of conditioning as a means of updating probability distributions when new evidence drives no event to certainty. His rule requires the stability of certain conditional probabilities through time. We tested this assumption (“invariance”) from the psychological point of view. In Experiment 1 participants offered probability estimates for events in Jeffrey’s candlelight example. Two further scenarios were investigated in Experiment 2, one in which invariance seems justified, the other in which it does not. Results were in (...)
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   16 citations  
  13. On the psychology of vague predicates.Nicolao Bonini, Daniel Osherson, Riccardo Viale & Timothy Williamson - 1999 - Mind and Language 14 (4):377–393.
    Most speakers experience unclarity about the application of predicates like tall and red to liminal cases. We formulate alternative psychological hypotheses about the nature of this unclarity, and report experiments that provide a partial test of them. A psychologized version of the ‘vagueness-as-ignorance’ theory is then advanced and defended.
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   25 citations  
  14. Updating: Learning versus supposing.Jiaying Zhao, Vincenzo Crupi, Katya Tentori, Branden Fitelson & Daniel Osherson - 2012 - Cognition 124 (3):373-378.
  15. Aggregating disparate estimates of chance.Daniel Osherson - manuscript
    We consider a panel of experts asked to assign probabilities to events, both logically simple and complex. The events evaluated by different experts are based on overlapping sets of variables but may otherwise be distinct. The union of all the judgments will likely be probabilistic incoherent. We address the problem of revising the probability estimates of the panel so as to produce a coherent set that best represents the group’s expertise.
     
    Export citation  
     
    Bookmark   14 citations  
  16. Preference based on reasons.Daniel Osherson & Scott Weinstein - 2012 - Review of Symbolic Logic 5 (1):122-147.
    We describe a logic of preference in which modal connectives reflect reasons to desire that a sentence be true. Various conditions on models are introduced and analyzed.
    Direct download (7 more)  
     
    Export citation  
     
    Bookmark   9 citations  
  17. A different conjunction fallacy.Nicolao Bonini, Katya Tentori & Daniel Osherson - 2004 - Mind and Language 19 (2):199–210.
    Because the conjunction pandq implies p, the value of a bet on pandq cannot exceed the value of a bet on p at the same stakes. We tested recognition of this principle in a betting paradigm that (a) discouraged misreading p as pandnotq, and (b) encouraged genuinely conjunctive reading of pandq. Frequent violations were nonetheless observed. The findings appear to discredit the idea that most people spontaneously integrate the logic of conjunction into their assessments of chance.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   16 citations  
  18.  60
    Some origins of belief.Daniel N. Osherson, Edward E. Smith & Eldar B. Shafir - 1986 - Cognition 24 (3):197-224.
  19.  66
    Identification in the limit of first order structures.Daniel Osherson & Scott Weinstein - 1986 - Journal of Philosophical Logic 15 (1):55 - 81.
  20.  43
    Language and the ability to evaluate contradictions and tautologies.Daniel N. Osherson & Ellen Markman - 1974 - Cognition 3 (3):213-226.
  21. On the provenance of judgments of conditional probability.Jiaying Zhao, Anuj Shah & Daniel Osherson - 2009 - Cognition 113 (1):26-36.
  22.  63
    Default Probability.Daniel N. Osherson, Joshua Stern, Ormond Wilkie, Michael Stob & Edward E. Smith - 1991 - Cognitive Science 15 (2):251-269.
    No categories
    Direct download  
     
    Export citation  
     
    Bookmark   13 citations  
  23.  58
    On typicality and vagueness.Daniel Osherson & Edward E. Smith - 1997 - Cognition 64 (2):189-206.
  24. Mechanical learners pay a price for Bayesianism.Daniel N. Osherson, Michael Stob & Scott Weinstein - 1988 - Journal of Symbolic Logic 53 (4):1245-1251.
  25.  57
    Evidential diversity and premise probability in young children's inductive judgment.Yafen Lo, Ashley Sides, Joseph Rozelle & Daniel Osherson - 2002 - Cognitive Science 26 (2):181-206.
    A familiar adage in the philosophy of science is that general hypotheses are better supported by varied evidence than by uniform evidence. Several studies suggest that young children do not respect this principle, and thus suffer from a defect in their inductive methodology. We argue that the diversity principle does not have the normative status that psychologists attribute to it, and should be replaced by a simple rule of probability. We then report experiments designed to detect conformity to the latter (...)
    No categories
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   11 citations  
  26.  87
    Paradigms of truth detection.Daniel N. Osherson & Scott Weinstein - 1989 - Journal of Philosophical Logic 18 (1):1 - 42.
    Alternative models of idealized scientific inquiry are investigated and compared. Particular attention is devoted to paradigms in which a scientist is required to determine the truth of a given sentence in the structure giving rise to his data.
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   10 citations  
  27. Aggregating Large Sets of Probabilistic Forecasts by Weighted Coherent Adjustment.Guanchun Wang, Sanjeev R. Kulkarni & Daniel N. Osherson - unknown
    Stochastic forecasts in complex environments can benefit from combining the estimates of large groups of forecasters (“judges”). But aggregating multiple opinions faces several challenges. First, human judges are notoriously incoherent when their forecasts involve logically complex events. Second, individual judges may have specialized knowledge, so different judges may produce forecasts for different events. Third, the credibility of individual judges might vary, and one would like to pay greater attention to more trustworthy forecasts. These considerations limit the value of simple aggregation (...)
    Direct download  
     
    Export citation  
     
    Bookmark   6 citations  
  28. Invitation to Cognitive Science.E. E. Smith & D. N. Osherson (eds.) - 1995 - MIT Press.
     
    Export citation  
     
    Bookmark   6 citations  
  29.  36
    A note on superadditive probability judgment.Laura Macchi, Daniel Osherson & David H. Krantz - 1999 - Psychological Review 106 (1):210-214.
  30. Extrapolating human probability judgment.Daniel Osherson, Edward E. Smith, Tracy S. Myers, Eldar Shafir & Michael Stob - 1994 - Theory and Decision 36 (2):103-129.
    We advance a model of human probability judgment and apply it to the design of an extrapolation algorithm. Such an algorithm examines a person's judgment about the likelihood of various statements and is then able to predict the same person's judgments about new statements. The algorithm is tested against judgments produced by thirty undergraduates asked to assign probabilities to statements about mammals.
    Direct download (6 more)  
     
    Export citation  
     
    Bookmark   6 citations  
  31.  21
    Learning theory and natural language.D. Osherson - 1984 - Cognition 17 (1):1-28.
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   6 citations  
  32.  69
    The Relation Between Probability and Evidence Judgment: An Extension of Support Theory*†.David H. Krantz, Daniel Osherson & Nicolao Bonini - unknown
    We propose a theory that relates perceived evidence to numerical probability judgment. The most successful prior account of this relation is Support Theory, advanced in Tversky and Koehler. Support Theory, however, implies additive probability estimates for binary partitions. In contrast, superadditivity has been documented in Macchi, Osherson, and Krantz, and both sub- and superadditivity appear in the experiments reported here. Nonadditivity suggests asymmetry in the processing of focal and nonfocal hypotheses, even within binary partitions. We extend Support Theory by revising (...)
    Direct download  
     
    Export citation  
     
    Bookmark   4 citations  
  33. Similarity and induction.Matthew Weber & Daniel Osherson - 2010 - Review of Philosophy and Psychology 1 (2):245-264.
    We advance a theory of inductive reasoning based on similarity, and test it on arguments involving mammal categories. To measure similarity, we quantified the overlap of neural activation in left Brodmann area 19 and the left ventral temporal cortex in response to pictures of different categories; the choice of of these regions is motivated by previous literature. The theory was tested against probability judgments for 40 arguments generated from 9 mammal categories and a common predicate. The results are interpreted in (...)
    Direct download (6 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  34. A universal inductive inference machine.Daniel N. Osherson, Michael Stob & Scott Weinstein - 1991 - Journal of Symbolic Logic 56 (2):661-672.
    A paradigm of scientific discovery is defined within a first-order logical framework. It is shown that within this paradigm there exists a formal scientist that is Turing computable and universal in the sense that it solves every problem that any scientist can solve. It is also shown that universal scientists exist for no regular logics that extend first-order logic and satisfy the Löwenheim-Skolem condition.
    Direct download (7 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  35. Order dependence and jeffrey conditionalization.Daniel Osherson - manuscript
    A glance at the sky raises my probability of rain to .7. As it happens, the conditional probabilities of each state given rain remain the same, and similarly for their conditional probabilities given no rain. As Jeffrey (1983, Ch. 11) points out, my new distribution P2 is therefore fixed by the law of total probability. For example, P2(RC) = P2(RC | R)P2(R)+P2(RC | ¯.
     
    Export citation  
     
    Bookmark   4 citations  
  36. A reason for theoretical terms.Haim Gaifman, DanielN Osherson & Scott Weinstein - 1990 - Erkenntnis 32 (2):149 - 159.
    The presence of nonobservational vocabulary is shown to be necessary for wide application of a conservative principle of theory revision.
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  37. An invitation to cognitive science, 3 vol.; vol. 1 : Language, vol. 2 : Visual cognition and action, vol. 3 : Thinking.D. Osherson, H. Lasknik, S. Kosslyn, J. M. Hollercbach & E. Smith - 1992 - Revue Philosophique de la France Et de l'Etranger 182 (1):123-125.
     
    Export citation  
     
    Bookmark   5 citations  
  38.  84
    Identifiable collections of countable structures.Daniel N. Osherson & Scott Weinstein - 1989 - Philosophy of Science 56 (1):94-105.
    A model of idealized scientific inquiry is presented in which scientists are required to infer the nature of the structure that makes true the data they examine. A necessary and sufficient condition is presented for scientific success within this paradigm.
    Direct download (8 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  39.  74
    Recognizing strong random reals.Daniel Osherson - 2008 - Review of Symbolic Logic 1 (1):56-63.
    1. Characterizing randomness. Consider a physical process that, if suitably idealized, generates an indefinite sequence of independent random bits. One such process might be radioactive decay of a lump of uranium whose mass is kept at just the level needed to ensure that the probability is one-half that no alpha particle is emitted in the nth microsecond of the experiment. Let us think of the bits as drawn from {0, 1} and denote the resulting sequence by x with coordinates x0, (...)
    Direct download (9 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  40.  46
    Three conditions on conceptual naturalness.Daniel N. Osherson - 1978 - Cognition 6 (4):263-289.
  41.  96
    Scientific discovery based on belief revision.Eric Martin & Daniel Osherson - 1997 - Journal of Symbolic Logic 62 (4):1352-1370.
    Scientific inquiry is represented as a process of rational hypothesis revision in the face of data. For the concept of rationality, we rely on the theory of belief dynamics as developed in [5, 9]. Among other things, it is shown that if belief states are left unclosed under deductive logic then scientific theories can be expanded in a uniform, consistent fashion that allows inquiry to proceed by any method of hypothesis revision based on "kernel" contraction. In contrast, if belief states (...)
    Direct download (8 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  42.  12
    Scientific discovery based on belief revision.Eric Martin & Daniel Osherson - 1997 - Journal of Symbolic Logic 62 (4):1352-1370.
    Scientific inquiry is represented as a process of rational hypothesis revision in the face of data. For the concept of rationality, we rely on the theory of belief dynamics as developed in [5, 9]. Among other things, it is shown that if belief states are left unclosed under deductive logic then scientific theories can be expanded in a uniform, consistent fashion that allows inquiry to proceed by any method of hypothesis revision based on “kernel” contraction. In contrast, if belief states (...)
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  43.  90
    A note on formal learning theory.Daniel N. Osherson & Scott Weinstein - 1982 - Cognition 11 (1):77-88.
    No categories
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  44.  50
    Category-based updating.Jiaying Zhao & Daniel Osherson - 2014 - Thinking and Reasoning 20 (1):1-15.
  45. Evans, J. St. BT, 165.V. Girotto, D. Osherson, R. de OverHastie, N. Pennington, S. Iwasaki, P. N. Johnson-Laird, J. Klayman, P. Legrenzi & E. Shafir - 1993 - Cognition 49:299.
    No categories
     
    Export citation  
     
    Bookmark   3 citations  
  46.  67
    A Source of Bayesian Priors.Daniel Osherson, Edward E. Smith, Eldar Shafir, Antoine Gualtierotti & Kevin Biolsi - 1995 - Cognitive Science 19 (3):377-405.
    Establishing reasonable, prior distributions remains a significant obstacle for the construction of probabilistic expert systems. Human assessment of chance is often relied upon for this purpose, but this has the drawback of being inconsistent with axioms of probability. This article advances a method for extracting a coherent distribution of probability from human judgment. The method is based on a psychological model of probabilistic reasoning, followed by a correction phase using linear programming.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   3 citations  
  47.  53
    Coherent probability from incoherent judgment.Daniel Osherson, David Lane, Peter Hartley & Richard R. Batsell - 2001 - Journal of Experimental Psychology: Applied 7 (1):3.
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   3 citations  
  48.  56
    Extracting the coherent core of human probability judgement: a research program for cognitive psychology.Daniel Osherson, Eldar Shafir & Edward E. Smith - 1994 - Cognition 50 (1-3):299-313.
  49. Thinking, vol. 3 de.D. N. Osherson & E. E. Smith - 1990 - In Daniel N. Osherson & Edward E. Smith (eds.), An Invitation to Cognitive Science. MIT Press.
     
    Export citation  
     
    Bookmark   3 citations  
  50.  67
    The conjunction fallacy: a misunderstanding about conjunction?Katya Tentori, Nicolao Bonini & Daniel Osherson - 2004 - Cognitive Science 28 (3):467-477.
    It is easy to construct pairs of sentences X, Y that lead many people to ascribe higher probability to the conjunction X‐and‐Y than to the conjuncts X, Y. Whether an error is thereby committed depends on reasoners' interpretation of the expressions “probability” and “and.” We report two experiments designed to clarify the normative status of typical responses to conjunction problems.
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   3 citations  
1 — 50 / 100