Search results for 'Joshua D. Goodman' (try it on Scholar)

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  1.  15
    Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman (2012). Bootstrapping in a Language of Thought: A Formal Model of Numerical Concept Learning. Cognition 123 (2):199-217.
  2.  10
    Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman (forthcoming). Bootstrapping in a Language of Thought: A Formal Model of Conceptual Change in Number Word Learning. Cognition.
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  3.  6
    Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman (2010). Beyond Boolean Logic: Exploring Representation Languages for Learning Complex Concepts. In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society 859--864.
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  4.  12
    Noah D. Goodman, Joshua B. Tenenbaum, Jacob Feldman & Thomas L. Griffiths (2008). A Rational Analysis of Rule‐Based Concept Learning. Cognitive Science 32 (1):108-154.
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  5.  6
    Laura E. Schulz, Noah D. Goodman, Joshua B. Tenenbaum & Adrianna C. Jenkins (2008). Going Beyond the Evidence: Abstract Laws and Preschoolers’ Responses to Anomalous Data. Cognition 109 (2):211-223.
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  6.  34
    Charles Kemp, Noah D. Goodman & Joshua B. Tenenbaum (2010). Learning to Learn Causal Models. Cognitive Science 34 (7):1185-1243.
    Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the (...)
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  7.  63
    Leah Henderson, Noah D. Goodman, Joshua B. Tenenbaum & James F. Woodward (2010). The Structure and Dynamics of Scientific Theories: A Hierarchical Bayesian Perspective. Philosophy of Science 77 (2):172-200.
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  8.  5
    Noah D. Goodman, Chris L. Baker & Joshua B. Tenenbaum (2009). Cause and Intent: Social Reasoning in Causal Learning. In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society. 2759--2764.
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  9.  14
    Charles Kemp, Noah D. Goodman & Joshua B. Tenenbaum (2007). Learning Causal Schemata. In McNamara D. S. & Trafton J. G. (eds.), Proceedings of the 29th Annual Cognitive Science Society. Cognitive Science Society 389--394.
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  10.  7
    Michael C. Frank, Noah D. Goodman, Peter Lai & Joshua B. Tenenbaum (2009). Informative Communication in Word Production and Word Learning. In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.
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  11.  12
    Lauren A. Schmidt, Noah D. Goodman, David Barner & Joshua B. Tenenbaum (2009). How Tall is Tall? Compositionality, Statistics, and Gradable Adjectives. In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.
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  12. Denis M. Walsh, Leah Henderson, Noah D. Goodman, Joshua B. Tenenbaum, James F. Woodward, Hannes Leitgeb, Richard Pettigrew, Brad Weslake & John Kulvicki (2010). 1. Not a Sure Thing: Fitness, Probability, and Causation Not a Sure Thing: Fitness, Probability, and Causation (Pp. 147-171). [REVIEW] Philosophy of Science 77 (2).
     
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  13.  2
    Noah D. Goodman, Joshua B. Tenenbaum, Thomas L. Griffiths & Jacob Feldman (2008). Compositionality in Rational Analysis: Grammar-Based Induction for Concept Learning. In Nick Chater & Mike Oaksford (eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science. OUP Oxford
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  14. Noah D. Goodman, Joshua B. Tenenbaum, Thomas L. Griffiths & Feldman & Jacob (2008). Compositionality in Rational Analysis: Grammar-Based Induction for Concept Learning. In Nick Chater & Mike Oaksford (eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science. OUP Oxford
     
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  15.  2
    M. D. Goodman (1999). D. W. R OLLER : The Building Program of Herod the Great . Pp. Xvii + 351, Maps, Figs. Berkeley, Los Angeles, and London: University of California Press, 1998. Cased, £37.50/$50. ISBN: 0-520-20934-. [REVIEW] The Classical Review 49 (01):291-.
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  16. Lenn E. Goodman & D. Gregory Caramenico (2014). Coming to Mind: The Soul and its Body. University of Chicago Press.
    How should we speak of bodies and souls? In _Coming to Mind_, Lenn E. Goodman and D. Gregory Caramenico pick their way through the minefields of materialist reductionism to present the soul not as the brain’s rival but as its partner. What acts, they argue, is what is real. The soul is not an ethereal wisp but a lively subject, emergent from the body but inadequately described in its terms. Rooted in some of the richest philosophical and intellectual (...)
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  17.  6
    Martin Goodman (1995). D. Noy: Jewish Inscriptions of Western Europe. Volume I, Italy (Excluding the City of Rome), Spain and Gaul. Pp. Xxi+385; 32 Plates. Cambridge: Cambridge University Press, 1993. [REVIEW] The Classical Review 45 (01):204-.
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  18. Lenn Goodman (1990). Armstrong, D. M., "Universals: An Opinionated Introduction". [REVIEW] Mind 99:473.
     
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  19. Nelson Goodman (1962). D. M. Armstrong's "Berkeley's Theory of Vision: A Critical Examination of Bishop Berkeley's Essay Towards a New Theory of Vision". [REVIEW] Philosophy and Phenomenological Research 23 (2):284.
  20. Nelson Goodman (2005). La Structure de L’Apparence. Vrin.
    Dans La structure de l’apparence, Nelson Goodman met en place les principaux thèmes philosophiques qui feront de lui un penseur singulier : constructivisme, nominalisme, phénoménalisme et pluralisme s’entrecroisent ici dans l’élaboration d’une pensée aussi subtile que complexe. Ce livre propose une première traduction d’un texte fondateur de la philosophie analytique.
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  21. David C. Goodman (1974). Towards a Mechanistic Philosophy. Open University Press.
    Unit 4. Goodman, D.C. God and nature in the philosophy of Descartes. --Unit 5. Brooke, J.H. Newton and the mechanistic universe.
     
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  22. Anthony D. Moulton, Richard A. Goodman, Kathy Cahill & Edward L. Baker (2002). Public Health Legal Preparedness for the 21st Century. Journal of Law, Medicine and Ethics 30 (2):141-143.
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  23.  10
    Steven D. Huett & David M. Goodman (2012). Levinas on Managed Care: The (a)Proximal, Faceless Third-Party and the Psychotherapeutic Dyad. Journal of Theoretical and Philosophical Psychology 32 (2):86-102.
    Emmanuel Levinas gave an account of radical, asymmetrical responsibility for the Other that is phenomenologically sensible in the proximity of face-to-face relation. This original arrangement, however, is not interminable. The approach of the third party equalizes and creates distance between self and Other by introducing ontology and epistemology. It is a necessary process of totalization that moves from a primordial ethics to justice and institutional fairness. However, Levinas was aware that the third party's presence brought with it a possible forgetting (...)
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  24.  1
    Anthony D. Moulton, Richard A. Goodman, Kathy Cahill & Edward L. Baker (2002). Public Health Legal Preparedness for the 21st Century. Journal of Law, Medicine & Ethics 30 (2):141-143.
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  25.  1
    Julie L. Gerberding, Anthony D. Moulton, Richard A. Goodman & Montrece McNeill Ransom (2003). Public Health Law, 2002?2003: Year of Achievement. Journal of Law, Medicine & Ethics 31 (4):482-484.
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  26. Julie L. Gerberding, Anthony D. Moulton, Richard A. Goodman & Montrece McNeill Ransom (2003). Public Health Law, 2002?2003: Year of Achievement. Journal of Law, Medicine and Ethics 31 (4):482-484.
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  27.  17
    Edward Vul, Noah Goodman, Thomas L. Griffiths & Joshua B. Tenenbaum (2014). One and Done? Optimal Decisions From Very Few Samples. Cognitive Science 38 (4):599-637.
    In many learning or inference tasks human behavior approximates that of a Bayesian ideal observer, suggesting that, at some level, cognition can be described as Bayesian inference. However, a number of findings have highlighted an intriguing mismatch between human behavior and standard assumptions about optimality: People often appear to make decisions based on just one or a few samples from the appropriate posterior probability distribution, rather than using the full distribution. Although sampling-based approximations are a common way to implement Bayesian (...)
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  28.  37
    Noah D. Goodman & Andreas Stuhlmüller (2013). Knowledge and Implicature: Modeling Language Understanding as Social Cognition. Topics in Cognitive Science 5 (1):173-184.
    Is language understanding a special case of social cognition? To help evaluate this view, we can formalize it as the rational speech-act theory: Listeners assume that speakers choose their utterances approximately optimally, and listeners interpret an utterance by using Bayesian inference to “invert” this model of the speaker. We apply this framework to model scalar implicature (“some” implies “not all,” and “N” implies “not more than N”). This model predicts an interaction between the speaker's knowledge state and the listener's interpretation. (...)
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  29.  5
    Elizabeth Bonawitz, Patrick Shafto, Hyowon Gweon, Noah D. Goodman, Elizabeth Spelke & Laura Schulz (2011). The Double-Edged Sword of Pedagogy: Instruction Limits Spontaneous Exploration and Discovery. Cognition 120 (3):322-330.
  30.  10
    Thomas L. Griffiths, Falk Lieder & Noah D. Goodman (2015). Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic. Topics in Cognitive Science 7 (2):217-229.
    Marr's levels of analysis—computational, algorithmic, and implementation—have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push the (...)
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  31.  6
    Nick Chater, Noah Goodman, Thomas L. Griffiths, Charles Kemp, Mike Oaksford & Joshua B. Tenenbaum (2011). The Imaginary Fundamentalists: The Unshocking Truth About Bayesian Cognitive Science. Behavioral and Brain Sciences 34 (4):194-196.
    If Bayesian Fundamentalism existed, Jones & Love's (J&L's) arguments would provide a necessary corrective. But it does not. Bayesian cognitive science is deeply concerned with characterizing algorithms and representations, and, ultimately, implementations in neural circuits; it pays close attention to environmental structure and the constraints of behavioral data, when available; and it rigorously compares multiple models, both within and across papers. J&L's recommendation of Bayesian Enlightenment corresponds to past, present, and, we hope, future practice in Bayesian cognitive science.
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  32.  4
    Anthony D. Moulton, Richard N. Gottfried, Richard A. Goodman, Anne M. Murphy & Raymond D. Rawson (2003). What Is Public Health Legal Preparedness? Journal of Law, Medicine & Ethics 31 (4):672-683.
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  33.  8
    Daniel Lassiter & Noah D. Goodman (forthcoming). Adjectival Vagueness in a Bayesian Model of Interpretation. Synthese:1-36.
    We derive a probabilistic account of the vagueness and context-sensitivity of scalar adjectives from a Bayesian approach to communication and interpretation. We describe an iterated-reasoning architecture for pragmatic interpretation and illustrate it with a simple scalar implicature example. We then show how to enrich the apparatus to handle pragmatic reasoning about the values of free variables, explore its predictions about the interpretation of scalar adjectives, and show how this model implements Edgington’s Vagueness: a reader, 1997) account of the sorites paradox, (...)
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  34.  6
    N. Noy, S. Bickel, E. Zion-Golumbic, M. Harel, T. Golan, I. Davidesco, C. A. Schevon, G. M. McKhann, R. R. Goodman, C. E. Schroeder, A. D. Mehta & R. Malach (2015). Ignition’s Glow: Ultra-Fast Spread of Global Cortical Activity Accompanying Local “Ignitions” in Visual Cortex During Conscious Visual Perception. Consciousness and Cognition 35:206-224.
  35.  1
    Claire Cook, Noah D. Goodman & Laura E. Schulz (2011). Where Science Starts: Spontaneous Experiments in Preschoolers’ Exploratory Play. Cognition 120 (3):341-349.
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  36.  59
    Nicolas D. Goodman (1978). Relativized Realizability in Intuitionistic Arithmetic of All Finite Types. Journal of Symbolic Logic 43 (1):23-44.
  37. Anthony D. Moulton, Richard N. Gottfried, Richard A. Goodman, Anne M. Murphy & Raymond D. Rawson (2003). What Is Public Health Legal Preparedness? Journal of Law, Medicine and Ethics 31 (4):672-683.
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  38.  12
    Justine T. Kao, Roger Levy & Noah D. Goodman (2015). A Computational Model of Linguistic Humor in Puns. Cognitive Science 40 (1).
    Humor plays an essential role in human interactions. Precisely what makes something funny, however, remains elusive. While research on natural language understanding has made significant advancements in recent years, there has been little direct integration of humor research with computational models of language understanding. In this paper, we propose two information-theoretic measures—ambiguity and distinctiveness—derived from a simple model of sentence processing. We test these measures on a set of puns and regular sentences and show that they correlate significantly with human (...)
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  39.  5
    Micah B. Goldwater, Noah D. Goodman, Stephen Wechsler & Gregory L. Murphy (2009). Relational and Role-Governed Categories: Views From Psychology, Computational Modeling, and Linguistics. In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.
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  40. Allan Bäck, Robert Bolton, J. D. G. Evans, Michael Ferejohn, Eugene Garver, Lenn E. Goodman, Edward Halper, Martha Husain, Gareth Matthews & Robin Smith (1999). From Puzzles to Principles?: Essays on Aristotle's Dialectic. Lexington Books.
    Scholars of classical philosophy have long disputed whether Aristotle was a dialectical thinker. Most agree that Aristotle contrasts dialectical reasoning with demonstrative reasoning, where the former reasons from generally accepted opinions and the latter reasons from the true and primary. Starting with a grasp on truth, demonstration never relinquishes it. Starting with opinion, how could dialectical reasoning ever reach truth, much less the truth about first principles? Is dialectic then an exercise that reiterates the prejudices of one's times and at (...)
     
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  41.  3
    Gregory Scontras, Peter Graff & Noah D. Goodman (2012). Comparing Pluralities. Cognition 123 (1):190-197.
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  42. Nelson Goodman, J. D. Mabbott, Dorothy Emmet, J. P. Day, A. R. Manser & B. F. McGuinness (1958). New Books. [REVIEW] Mind 67 (265):107-119.
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  43.  69
    Nicolas D. Goodman (1973). The Faithfulness of the Interpretation of Arithmetic in the Theory of Constructions. Journal of Symbolic Logic 38 (3):453-459.
  44.  65
    Nicolas D. Goodman (1976). The Theory of the Gödel Functionals. Journal of Symbolic Logic 41 (3):574-582.
  45.  10
    Leon Bergen & Noah D. Goodman (2015). The Strategic Use of Noise in Pragmatic Reasoning. Topics in Cognitive Science 7 (2):336-350.
    We combine two recent probabilistic approaches to natural language understanding, exploring the formal pragmatics of communication on a noisy channel. We first extend a model of rational communication between a speaker and listener, to allow for the possibility that messages are corrupted by noise. In this model, common knowledge of a noisy channel leads to the use and correct understanding of sentence fragments. A further extension of the model, which allows the speaker to intentionally reduce the noise rate on a (...)
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  46.  8
    Nicolas D. Goodman (1981). The Logic of Contradiction. Mathematical Logic Quarterly 27 (8‐10):119-126.
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  47.  23
    Nicolas D. Goodman (1990). Mathematics as Natural Science. Journal of Symbolic Logic 55 (1):182-193.
  48.  10
    Nicolas D. Goodman (1984). Epistemic Arithmetic is a Conservative Extension of Intuitionistic Arithmetic. Journal of Symbolic Logic 49 (1):192-203.
  49.  4
    Nicolas D. Goodman (1981). The Logic of Contradiction. Zeitschrift fur mathematische Logik und Grundlagen der Mathematik 27 (8-10):119-126.
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  50.  5
    Desmond C. Ong, Jamil Zaki & Noah D. Goodman (2015). Affective Cognition: Exploring Lay Theories of Emotion. Cognition 143:141-162.
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