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  1. 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 (...)
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  • Robust reasoning: integrating rule-based and similarity-based reasoning.Ron Sun - 1995 - Artificial Intelligence 75 (2):241-295.
  • When explanations compete: the role of explanatory coherence on judgements of likelihood.Steven A. Sloman - 1994 - Cognition 52 (1):1-21.
    The likelihood of a statement is often derived by generating an explanation for it and evaluating the plausibility of the explanation. The explanation discounting principle states that people tend to focus on a single explanation; alternative explanations compete with the effect of reducing one another’s credibility. Two experiments tested the hypothesis that this principle applies to inductive inferences concerning the properties of everyday categories. In both experiments, subjects estimated the probability of a series of statements and the conditional probabilities of (...)
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  • Similarity as an explanatory construct.Steven A. Sloman & Lance J. Rips - 1998 - Cognition 65 (2-3):87-101.
  • The cognitive processes in informal reasoning.Victoria F. Shaw - 1996 - Thinking and Reasoning 2 (1):51 – 80.
    Two experiments investigated the factors that people consider when evaluating informal arguments in newspaper and magazine editorials. Experiment 1 showed that subjects were more likely to object to the truth of the premises and the conclusions of an argument than to the strength of the link between them. Experiment 1 also revealed two manipulations that helped subjects object to the link between premises and conclusions: rating how well the premises support the conclusions and rating the believability of the premises and (...)
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  • On language and connectionism: Analysis of a parallel distributed processing model of language acquisition.Steven Pinker & Alan Prince - 1988 - Cognition 28 (1-2):73-193.
  • 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.
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  • A hypothesis-assessment model of categorical argument strength.John McDonald, Mark Samuels & Janet Rispoli - 1996 - Cognition 59 (2):199-217.
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  • 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 (...)
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  • Reply to the commentators on a model theory of induction.Philip N. Johnson‐Laird - 1994 - International Studies in the Philosophy of Science 8 (1):73 – 96.
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  • Rules and illusions: A critical study of Rips's the psychology of proof. [REVIEW]Philip N. Johnson-Laird - 1997 - Minds and Machines 7 (3):387-407.
  • Mental models and probabilistic thinking.Philip N. Johnson-Laird - 1994 - Cognition 50 (1-3):189-209.
  • A model theory of induction.Philip N. Johnson‐Laird - 1994 - International Studies in the Philosophy of Science 8 (1):5 – 29.
    Abstract Theories of induction in psychology and artificial intelligence assume that the process leads from observation and knowledge to the formulation of linguistic conjectures. This paper proposes instead that the process yields mental models of phenomena. It uses this hypothesis to distinguish between deduction, induction, and creative forms of thought. It shows how models could underlie inductions about specific matters. In the domain of linguistic conjectures, there are many possible inductive generalizations of a conjecture. In the domain of models, however, (...)
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  • Reasoning from uncertain premises.Christian George - 1997 - Thinking and Reasoning 3 (3):161 – 189.
    Previous studies have shown that 1 participants are reluctant to accept a conclusion as certainly true when it is derived from a valid conditional argument that includes a doubtful premise, and 2 participants typically link the degree of uncertainty found in a given premise set to its conclusion. Two experiments were designed to further investigate these phenomena. Ninety adult participants in Experiment 1 were first asked to judge the validity of three conditional arguments Modus Ponens, Denial of the Antecedent, and (...)
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  • From similarity to chance.Daniel Osherson - manuscript
    “In reality, all arguments from experience are founded on the similarity which we discover among natural objects, and by which we are induced to expect effects similar to those which we have found to follow from such objects. ... From causes which appear similar we expect similar effects.”.
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