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  1. Alison Gopnik, Clark Glymour, David M. Sobel & Laura E. Schultz, Causal Learning in Children: Causal Maps and Bayes Nets.
    We outline a cognitive and computational account of causal learning in children. We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent representation of the causal relations among events. This kind of knowledge can be perspicuously represented by the formalism of directed graphical causal models, or “Bayes nets”. Human causal learning and inference may involve computations similar to those for learnig causal Bayes nets and for predicting with (...)
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  2. Alison Gopnik, Causal Learning Across Domains.
    Five studies investigated (a) children’s ability to use the dependent and independent probabilities of events to make causal inferences and (b) the interaction between such inferences and domain-specific knowledge. In Experiment 1, preschoolers used patterns of dependence and independence to make accurate causal inferences in the domains of biology and psychology. Experiment 2 replicated the results in the domain of biology with a more complex pattern of conditional dependencies. In Experiment 3, children used evidence about patterns of dependence and independence (...)
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  3. Alison Gopnik, Sorting and Acting with Objects in Early Childhood: An Exploration of the Use of Causal Cues.
    Three experiments investigated young children’s ability to use a causal property, making a machine light up and play music, to sort objects together (sorting task), and then to predict how to make the machine work (action task). The results show that the performance of 30-month-old children is guided in both tasks by the causal properties of the objects. This suggests that causal information is used to categorize objects even in a task that does not involve naming. The causal interpretation of (...)
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  4. Alison Gopnik, Young Children Infer Causal Strength From Probabilities and Interventions.
    Word count (excluding abstract and references): 2,498 words. Address for correspondence: T. Kushnir, Psychology Department, University of California, 3210 Tolman Hall #1650, Berkeley, CA 94720-1650. Phone: 510-205-9847. Fax: 510-642- 5293. E-mail: tkushnir@berkeley.edu.
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  5. Christopher G. Lucas, Sophie Bridgers, Thomas L. Griffiths & Alison Gopnik (2014). When Children Are Better (or at Least More Open-Minded) Learners Than Adults: Developmental Differences in Learning the Forms of Causal Relationships. Cognition 131 (2):284-299.
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  6. Caren M. Walker, Tania Lombrozo, Cristine H. Legare & Alison Gopnik (2014). Explaining Prompts Children to Privilege Inductively Rich Properties. Cognition 133 (2):343-357.
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  7. Stephanie Denison, Elizabeth Bonawitz, Alison Gopnik & Thomas L. Griffiths (2013). Rational Variability in Children's Causal Inferences: The Sampling Hypothesis. Cognition 126 (2):285-300.
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  8. Andrew N. Ivieltzoff & Alison Gopnik (2013). Learning About the Mind From Evidence: Children's Development of Intuitive. In Simon Baron-Cohen, Michael Lombardo & Helen Tager-Flusberg (eds.), Understanding Other Minds: Perspectives From Developmental Social Neuroscience. Oup Oxford. 19.
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  9. Deena S. Weisberg & Alison Gopnik (2013). Pretense, Counterfactuals, and Bayesian Causal Models: Why What Is Not Real Really Matters. Cognitive Science 37 (7):1368-1381.
    Young children spend a large portion of their time pretending about non-real situations. Why? We answer this question by using the framework of Bayesian causal models to argue that pretending and counterfactual reasoning engage the same component cognitive abilities: disengaging with current reality, making inferences about an alternative representation of reality, and keeping this representation separate from reality. In turn, according to causal models accounts, counterfactual reasoning is a crucial tool that children need to plan for the future and learn (...)
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  10. Daphna Buchsbaum, Alison Gopnik, Thomas L. Griffiths & Patrick Shafto (2011). Children's Imitation of Causal Action Sequences is Influenced by Statistical and Pedagogical Evidence. Cognition 120 (3):331-340.
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  11. Alison Gopnik (2011). A Unified Account of Abstract Structure and Conceptual Change: Probabilistic Models and Early Learning Mechanisms. Behavioral and Brain Sciences 34 (3):129-130.
    We need not propose, as Carey does, a radical discontinuity between core cognition, which is responsible for abstract structure, and language and which are responsible for learning and conceptual change. From a probabilistic models view, conceptual structure and learning reflect the same principles, and they are both in place from the beginning.
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  12. Alison Gopnik (2011). Probabilistic Models as Theories of Children's Minds. Behavioral and Brain Sciences 34 (4):200-201.
    My research program proposes that children have representations and learning mechanisms that can be characterized as causal models of the world Bayesian Fundamentalism.”.
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  13. Thomas L. Griffiths, David M. Sobel, Joshua B. Tenenbaum & Alison Gopnik (2011). Bayes and Blickets: Effects of Knowledge on Causal Induction in Children and Adults. Cognitive Science 35 (8):1407-1455.
    People are adept at inferring novel causal relations, even from only a few observations. Prior knowledge about the probability of encountering causal relations of various types and the nature of the mechanisms relating causes and effects plays a crucial role in these inferences. We test a formal account of how this knowledge can be used and acquired, based on analyzing causal induction as Bayesian inference. Five studies explored the predictions of this account with adults and 4-year-olds, using tasks in which (...)
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  14. Elizabeth Baraff Bonawitz, Darlene Ferranti, Rebecca Saxe, Alison Gopnik, Andrew N. Meltzoff, James Woodward & Laura E. Schulz (2010). Just Do It? Investigating the Gap Between Prediction and Action in Toddlers' Causal Inferences. Cognition 115 (1):104-117.
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  15. Alison Gopnik (2010). Could David Hume Have Known About Buddhism? Hume Studies 35 (1/2):5-28.
    Philosophers and Buddhist scholars have noted the affinities between David Hume�s empiricism and the Buddhist philosophical tradition. I show that it was possible for Hume to have had contact with Buddhist philosophical views. The link to Buddhism comes through the Jesuit scholars at the Royal College of La Fl�che. Charles Fran�ois Dolu was a Jesuit missionary who lived at the Royal College from 1723�1740, overlapping with Hume�s stay. He had extensive knowledge both of other religions and cultures and of scientific (...)
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  16. Alison Gopnik, Henry M. Wellman, Susan A. Gelman & Andrew N. Meltzoff (2010). A Computational Foundation for Cognitive Development: Comment on Griffths Et Al. And McLelland Et Al. Trends in Cognitive Sciences 14 (8):342-343.
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  17. Tamar Kushnir, Alison Gopnik, Chris Lucas & Laura Schulz (2010). Inferring Hidden Causal Structure. Cognitive Science 34 (1):148-160.
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  18. Chris Lucas, Alison Gopnik & Thomas L. Griffiths (2010). Developmental Differences in Learning the Forms of Causal Relationships. In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. 28--52.
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  19. Rachel Wu, Alison Gopnik, Daniel C. Richardson & Natasha Z. Kirkham (2010). Social Cues Support Learning About Objects From Statistics in Infancy. In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society.
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  20. Daphna Buchsbaum, Thomas L. Griffiths, Alison Gopnik & Dare Baldwin (2009). Learning From Actions and Their Consequences: Inferring Causal Variables From Continuous Sequences of Human Action. In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society. 134.
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  21. Alison Gopnik (2009). Rational Constructivism: A New Way to Bridge Rationalism and Empiricism. Behavioral and Brain Sciences 32 (2):208-209.
    Recent work in rational probabilistic modeling suggests that a kind of propositional reasoning is ubiquitous in cognition and especially in cognitive development. However, there is no reason to believe that this type of computation is necessarily conscious or resource-intensive.
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  22. John R. Anderson & Alison Gopnik, Marshall M. Weinberg Conference: The Future of Cognitive Science - Thursday Afternoon (Oct. 16, 2008) Session: John R. Anderson and Alison Gopnik. [REVIEW]
    Six leading experts speak about the future of cognitive science.
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  23. Alison Gopnik (2007). Why Babies Are More Conscious Than We Are. Behavioral and Brain Sciences 30 (5-6):503-504.
    Block argues for a method and a substantive thesis – that consciousness overflows accessibility. The method can help answer the question of what it is like to be a baby. Substantively, infant consciousness may be accessible in some ways but not others. But development itself can also add important methodological tools and substantive insights to the study of consciousness.
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  24. Alison Gopnik & Laura Schulz (eds.) (2007). Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press.
    Understanding causal structure is a central task of human cognition. Causal learning underpins the development of our concepts and categories, our intuitive theories, and our capacities for planning, imagination and inference. During the last few years, there has been an interdisciplinary revolution in our understanding of learning and reasoning: Researchers in philosophy, psychology, and computation have discovered new mechanisms for learning the causal structure of the world. This new work provides a rigorous, formal basis for theory theories of concepts and (...)
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  25. Thomas Richardson, Laura Schulz & Alison Gopnik (2007). Data-Mining Probabilists or Experimental Determinists. In Alison Gopnik & Laura Schulz (eds.), Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press. 208--230.
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  26. Laura Schulz, Tamar Kushnir & Alison Gopnik (2007). Learning From Doing: Intervention and Causal Inference. In Alison Gopnik & Laura Schulz (eds.), Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press. 67--85.
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  27. Alison Gopnik (2004). Children's Causal Inferences From Indirect Evidence: Backwards Blocking and Bayesian Reasoning in Preschoolers. Cognitive Science 28 (3):303-333.
    Previous research suggests that children can infer causal relations from patterns of events. However, what appear to be cases of causal inference may simply reduce to children recognizing relevant associations among events, and responding based on those associations. To examine this claim, in Experiments 1 and 2, children were introduced to a “blicket detector”, a machine that lit up and played music when certain objects were placed upon it. Children observed patterns of contingency between objects and the machine’s activation that (...)
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  28. Alison Gopnik (2004). Mechanisms of Theory Formation in Young Children. Trends in Cognitive Sciences 8 (8):371-377.
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  29. Alison Gopnik, Clark Glymour, David M. Sobel, Laura Schulz, Tamar Kushnir & David Danks, A Theory of Causal Learning in Children: Causal Maps and Bayes Nets.
    We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or “Bayes nets”. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children (...)
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  30. Alison Gopnik & Laura Schulz (2004). Questions for Future Research. Trends in Cognitive Sciences 8 (8):371-377.
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  31. Alison Gopnik (2003). The Theory Theory as an Alternative to the Innateness Hypothesis. In Louise M. Antony (ed.), Chomsky and His Critics. Blackwell. 238--254.
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  32. Alison Gopnik & Clark Glymour (2002). Causal Maps and Bayes Nets: A Cognitive and Computational Account of Theory-Formation. In Peter Carruthers, Stephen P. Stich & Michael Siegal (eds.), The Cognitive Basis of Science. Cambridge University Press. 117--132.
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  33. Daniel R. Ames, Eric D. Knowles, Michael W. Morris, Charles W. Kalish, Andrea D. Rosati & Alison Gopnik (2001). The Social Folk Theorist: Insights From Social and Cultural Psychology on The. In Bertram Malle, L. J. Moses & Dare Baldwin (eds.), Intentions and Intentionality: Foundations of Social Cognition. Mit Press.
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  34. Clark Glymour, Alison Gopnik, David M. Sobel & Laura E. Schulz, Causal Learning Mechanisms in Very Young Children: Two-, Three-, and Four-Year-Olds Infer Causal Relations From Patterns of Variation and Covariation.
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  35. Thierry Nazzi & Alison Gopnik (2001). Linguistic and Cognitive Abilities in Infancy: When Does Language Become a Tool for Categorization? Cognition 80 (3):B11-B20.
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  36. Andrea D. Rosati, Eric D. Knowles, Charles W. Kalish, Alison Gopnik, Daniel R. Ames & Michael W. Morris (2001). The Rocky Road From Acts to Dispositions: Insights for Attribution Theory From Developmental Research on Theories of Mind. In Bertram Malle, L. J. Moses & Dare Baldwin (eds.), Intentions and Intentionality: Foundations of Social Cognition. Mit Press.
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  37. George Bealer, Robert Cummings, Michael DePaul, Richard Foley, Alvin Goldman, Alison Gopnik, George Graham, Gary Gutting, Tery Horgan, Tamara Horowitz, Hilary Kornblith, Joel Pust, E. Rosch, Eldar Shafir, Stephen Stitch, Ernest Sosa & Edward Wisniewkski (1998). Rethinking Intuition: The Psychology of Intuition and its Role in Philosophical Inquiry. Rowman & Littlefield Publishers.
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  38. Alison Gopnik (1998). Explanation as Orgasm. Minds and Machines 8 (1):101-118.
    I argue that explanation should be thought of as the phenomenological mark of the operation of a particular kind of cognitive system, the theory-formation system. The theory-formation system operates most clearly in children and scientists but is also part of our everyday cognition. The system is devoted to uncovering the underlying causal structure of the world. Since this process often involves active intervention in the world, in the case of systematic experiment in scientists, and play in children, the cognitive system (...)
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  39. Alison Gopnik (1998). What Can Externalism Do for Psychologists? Behavioral and Brain Sciences 21 (1):73-74.
    I suggest several ways that externalism could influence psychological theorizing. Externalism could just capture our everyday intuitions about concepts and meanings. More profoundly, it could enter into psychology through evolutionary theory, guide our hypotheses about conceptual abilities, and, most significantly, it could influence our accounts of learning and conceptual change.
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  40. Alison Gopnik & Andrew N. Meltzoff (1998). Theories Vs. Modules: To the Max and Beyond: A Reply to Poulin-Dubois and to Stich and Nichols. Mind and Language 13 (3):450-456.
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  41. Alison Gopnik & Eric Schwitzgebel (1998). Whose Concepts Are They, Anyway? The Role of Philosophical Intuition in Empirical Psychology. In M. R. DePaul & William Ramsey (eds.), Rethinking Intuition. Lanham: Rowman and Littlefield. 75--91.
    This chapter examines several ways in which philosophical attention to intuition can contribute to empirical scientific psychology. The authors then discuss one prevalent misuse of intuition. An unspoken assumption of much argumentation in the philosophy of mind has been that to articulate our folk psychological intuitions, our ordinary concepts of belief, truth, meaning, and so forth, is itself sufficient to give a theoretical account of what belief, truth, meaning, and so forth, actually are. It is believed that this assumption rests (...)
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  42. Herbert A. Simon, Discovering Explanations, Clark Glymour, Andy Clark, Twisted Tales, Alison Gopnik & Explanation as Orgasm (1998). Cognition and Explanation. Cognition 8 (1).
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  43. Alison Gopnik (1997). The Scientist as Child. Philosophy of Science 63 (4):485-514.
    This paper argues that there are powerful similarities between cognitive development in children and scientific theory change. These similarities are best explained by postulating an underlying abstract set of rules and representations that underwrite both types of cognitive abilities. In fact, science may be successful largely because it exploits powerful and flexible cognitive devices that were designed by evolution to facilitate learning in young children. Both science and cognitive development involve abstract, coherent systems of entities and rules, theories. In both (...)
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  44. Alison Gopnik (1997). Words, Thoughts, and Theories. Mit Press.
    Recently, the theory theory has led to much interesting research. However, this is the first book to look at the theory in extensive detail and to systematically contrast it with other theories.
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  45. Alison Gopnik (1996). Philosophy of Science. Philosophy of Science 63 (4).
    Opinion. Argues that there are similarities between cognitive development in children and scientific theory change. How these similarities are best explained; Why science may be successful; What science and cognitive development involve; Definition of a theory; Details of theories in childhood.
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  46. Alison Gopnik (1996). Reply to Commentators. Philosophy of Science 63 (4):552-561.
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  47. Alison Gopnik (1996). 11 Theories and Modules; Creation Myths, Developmental Realities, and Neurath's Boat. In Peter Carruthers & Peter K. Smith (eds.), Theories of Theories of Mind. Cambridge University Press. 169.
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  48. Alison Gopnik (1995). How to Understand Beliefs. Behavioral and Brain Sciences 18 (2):398.
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  49. Alison Gopnik & Andrew N. Meltzoff (1994). Minds, Bodies, and Persons: Young Children's Understanding of the Self and Others as Reflected in Imitation and Theory of Mind Research. In S. T. Parker, R. Mitchell & M. L. Boccia (eds.), Self-Awareness in Animals and Humans: Developmental Perspectives. Cambridge University Press.
     
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  50. Alison Gopnik (1993). How We Know Our Minds: The Illusion of First-Person Knowledge of Intentionality. Behavioral and Brain Sciences 16 (1):1.
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