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Steven A. Sloman [30]Steven Sloman [8]
  1. Constantinos Hadjichristidis, Steven A. Sloman & David E. Over (2014). Categorical Induction From Uncertain Premises: Jeffrey's Doesn't Completely Rule. 20 (4):405-431.
    (2014). Categorical induction from uncertain premises: Jeffrey's doesn't completely rule. Thinking & Reasoning: Vol. 20, No. 4, pp. 405-431. doi: 10.1080/13546783.2014.884510.
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  2. Steven Sloman (2014). Comments on Quantum Probability Theory. Topics in Cognitive Science 6 (1):47-52.
    Quantum probability theory (QP) is the best formal representation available of the most common form of judgment involving attribute comparison (inside judgment). People are capable, however, of judgments that involve proportions over sets of instances (outside judgment). Here, the theory does not do so well. I discuss the theory both in terms of descriptive adequacy and normative appropriateness.
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  3. Jean-François Bonnefon & Steven A. Sloman (2013). The Causal Structure of Utility Conditionals. Cognitive Science 37 (1):193-209.
    The psychology of reasoning is increasingly considering agents' values and preferences, achieving greater integration with judgment and decision making, social cognition, and moral reasoning. Some of this research investigates utility conditionals, ‘‘if p then q’’ statements where the realization of p or q or both is valued by some agents. Various approaches to utility conditionals share the assumption that reasoners make inferences from utility conditionals based on the comparison between the utility of p and the expected utility of q. This (...)
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  4. Steven A. Sloman (2013). Counterfactuals and Causal Models: Introduction to the Special Issue. Cognitive Science 37 (6):969-976.
    Judea Pearl won the 2010 Rumelhart Prize in computational cognitive science due to his seminal contributions to the development of Bayes nets and causal Bayes nets, frameworks that are central to multiple domains of the computational study of mind. At the heart of the causal Bayes nets formalism is the notion of a counterfactual, a representation of something false or nonexistent. Pearl refers to Bayes nets as oracles for intervention, and interventions can tell us what the effect of action will (...)
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  5. Bénédicte Bes, Steven Sloman, Christopher G. Lucas & Éric Raufaste (2012). Non-Bayesian Inference: Causal Structure Trumps Correlation. Cognitive Science 36 (7):1178-1203.
    The study tests the hypothesis that conditional probability judgments can be influenced by causal links between the target event and the evidence even when the statistical relations among variables are held constant. Three experiments varied the causal structure relating three variables and found that (a) the target event was perceived as more probable when it was linked to evidence by a causal chain than when both variables shared a common cause; (b) predictive chains in which evidence is a cause of (...)
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  6. Steven A. Sloman, Philip M. Fernbach & Scott Ewing (2012). A Causal Model of Intentionality Judgment. Mind and Language 27 (2):154-180.
    We propose a causal model theory to explain asymmetries in judgments of the intentionality of a foreseen side-effect that is either negative or positive (Knobe, 2003). The theory is implemented as a Bayesian network relating types of mental states, actions, and consequences that integrates previous hypotheses. It appeals to two inferential routes to judgment about the intentionality of someone else's action: bottom-up from action to desire and top-down from character and disposition. Support for the theory comes from three experiments that (...)
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  7. Philip M. Fernbach, Adam Darlow & Steven A. Sloman (2011). When Good Evidence Goes Bad: The Weak Evidence Effect in Judgment and Decision-Making. Cognition 119 (3):459-467.
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  8. Philip M. Fernbach & Steven A. Sloman (2011). Don't Throw Out the Bayes with the Bathwater. Behavioral and Brain Sciences 34 (4):198-199.
    We highlight one way in which Jones & Love (J&L) misconstrue the Bayesian program: Bayesian models do not represent a rejection of mechanism. This mischaracterization obscures the valid criticisms in their article. We conclude that computational-level Bayesian modeling should not be rejected or discouraged a priori, but should be held to the same empirical standards as other models.
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  9. Clare R. Walsh & Steven A. Sloman (2011). Counterfactual and Generative Accounts of Causal Attribution. In Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.), Causality in the Sciences. Oxford University Press. 184.
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  10. Clare R. Walsh & Steven A. Sloman (2011). The Meaning of Cause and Prevent: The Role of Causal Mechanism. Mind and Language 26 (1):21-52.
    How do people understand questions about cause and prevent? Some theories propose that people affirm that A causes B if A's occurrence makes a difference to B's occurrence in one way or another. Other theories propose that A causes B if some quantity or symbol gets passed in some way from A to B. The aim of our studies is to compare these theories' ability to explain judgements of causation and prevention. We describe six experiments that compare judgements for causal (...)
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  11. Steven A. Sloman, Philip M. Fernbach & York Hagmayer (2010). Self-Deception Requires Vagueness. Cognition 115 (2):268-281.
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  12. Jeffrey Loewenstein, Chip Heath, Steven Sloman, Aron K. Barbey, Jared M. Hotaling, Max M. Louwerse, Rolf A. Zwaan, Sabine Stoll, Kirsten Abbot-Smith & Elena Lieven (2009). Subject Index to Volume 33. Cognitive Science 33:1526-1531.
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  13. Steven Sloman, Aron K. Barbey & Jared M. Hotaling (2009). A Causal Model Theory of the Meaning of Cause, Enable, and Prevent. Cognitive Science 33 (1):21-50.
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  14. Giorgio Gronchi & Steven A. Sloman (2008). Do Causal Beliefs Influence the Hot-Hand and the Gambler's Fallacy?. In. In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society. 1164--1168.
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  15. Aron K. Barbey & Steven A. Sloman (2007). Base-Rate Respect: From Ecological Rationality to Dual Processes. Behavioral and Brain Sciences 30 (3):241-254.
    The phenomenon of base-rate neglect has elicited much debate. One arena of debate concerns how people make judgments under conditions of uncertainty. Another more controversial arena concerns human rationality. In this target article, we attempt to unpack the perspectives in the literature on both kinds of issues and evaluate their ability to explain existing data and their conceptual coherence. From this evaluation we conclude that the best account of the data should be framed in terms of a dual-process model of (...)
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  16. Aron K. Barbey & Steven A. Sloman (2007). Base-Rate Respect: From Statistical Formats to Cognitive Structures. Behavioral and Brain Sciences 30 (3):287-292.
    The commentaries indicate a general agreement that one source of reduction of base-rate neglect involves making structural relations among relevant sets transparent. There is much less agreement, however, that this entails dual systems of reasoning. In this response, we make the case for our perspective on dual systems. We compare and contrast our view to the natural frequency hypothesis as formulated in the commentaries.
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  17. Philip M. Fernbach, Preston Linson-Gentry & Steven A. Sloman (2007). Causal Beliefs Influence the Perception of Temporal Order. In McNamara D. S. & Trafton J. G. (eds.), Proceedings of the 29th Annual Cognitive Science Society. Cognitive Science Society. 269--74.
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  18. York Hagmayer, Steven A. Sloman, David A. Lagnado & Michael R. Waldmann (2007). Causal Reasoning Through Intervention. In Alison Gopnik & Laura Schulz (eds.), Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press.
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  19. David A. Lagnado, Michael R. Waldmann, York Hagmayer & Steven A. Sloman (2007). Beyond Covariation. In Alison Gopnik & Laura Schulz (eds.), Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press.
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  20. Barbara C. Malt & Steven A. Sloman (2007). Artifact Categorization: The Good, the Bad, and the Ugly. In Eric Margolis & Stephen Laurence (eds.), Creations of the Mind: Theories of Artifacts and Their Representation. Oxford University Press. 85--123.
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  21. Barbara C. Malt & Steven A. Sloman (2007). Category Essence or Essentially Pragmatic? Creator's Intention in Naming and What's Really What. Cognition 105 (3):615-648.
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  22. Barbara C. Malt & Steven A. Sloman (2007). More Than Words, but Still Not Categorization. Cognition 105 (3):656-657.
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  23. Steven A. Sloman & York Hagmayer (2006). The Causal Psycho-Logic of Choice. Trends in Cognitive Sciences 10 (9):407-412.
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  24. Robert L. Goldstone, Steven A. Sloman, David A. Lagnado, Mark Steyvers, Joshua B. Tenenbaum, Saskia Jaarsveld, Cees van Leeuwen, Murray Shanahan, Terry Dartnall & Simon Dennis (2005). Subject Index to Volume 29. Cognitive Science 29:1093-1096.
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  25. Steven Sloman (2005). Avoiding Foolish Consistency. Behavioral and Brain Sciences 28 (1):33-34.
    In most cases, rule-governed relations and similarity relations can indeed be distinguished by the number of relevant features they require. This criterion is not sufficient, however, to explain other properties of the relations that have a more dichotomous character. I focus on the differential drive for consistency by inferential processes that draw on the two types of relations.
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  26. Steven Sloman (2005). Causal Models: How People Think About the World and Its Alternatives. OUP USA.
    Human beings are active agents who can think. To understand how thought serves action requires understanding how people conceive of the relation between cause and effect, that is, between action and outcome. -/- In cognitive terms, the question becomes one of how people construct and reason with the causal models we use to represent our world. A revolution is occuring in how statisticians, philosophers, and computer scientists answer this question. These fields have ushered in new insights about causal models by (...)
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  27. Steven A. Sloman & D. Lagnado (2005). The Problem of Induction. In K. Holyoak & B. Morrison (eds.), The Cambridge Handbook of Thinking and Reasoning. Cambridge Univ Pr. 95--116.
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  28. Steven A. Sloman & David A. Lagnado (2005). Do We “Do”? Cognitive Science 29 (1):5-39.
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  29. Constantinos Hadjichristidis, Steven Sloman, Rosemary Stevenson & David Over (2004). Feature Centrality and Property Induction. Cognitive Science 28 (1):45-74.
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  30. Barbara C. Malt, Steven A. Sloman & Silvia P. Gennari (2003). Speaking Versus Thinking About Objects and Actions. In Dedre Getner & Susan Goldin-Meadow (eds.), Language in Mind: Advances in the Study of Language and Thought. Mit Press. 81--112.
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  31. Steven A. Sloman, Bradley C. Love & Woo‐Kyoung Ahn (1998). Feature Centrality and Conceptual Coherence. Cognitive Science 22 (2):189-228.
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  32. Steven A. Sloman & Lance J. Rips (1998). Similarity as an Explanatory Construct. Cognition 65 (2-3):87-101.
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  33. Steven A. Sloman (1997). Explanatory Coherence and the Induction of Properties. Thinking and Reasoning 3 (2):81 – 110.
    Statements that share an explanation tend to lend inductive support to one another. For example, being told that Many furniture movers have a hard time financing a house increases the judged probability that Secretaries have a hard time financing a house. In contrast, statements with different explanations reduce one another s judged probability. Being told that Many furniture movers have bad backs decreases the judged probability that Secretaries have bad backs. I pose two questions concerning such discounting effects. First, does (...)
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  34. Steven A. Sloman (1994). Progress Within the Bounds of Memory. Behavioral and Brain Sciences 17 (4):679.
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  35. Steven A. Sloman (1994). When Explanations Compete: The Role of Explanatory Coherence on Judgements of Likelihood. Cognition 52 (1):1-21.
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  36. Steven Sloman (1993). Do Simple Associations Lead to Systematic Reasoning? Behavioral and Brain Sciences 16 (3):471.
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  37. Steven A. Sloman & Leon Sloman (1992). What Does Evolution Tell Us About Age Preferences? Behavioral and Brain Sciences 15 (1):110-111.
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  38. Steven A. Sloman (1991). Part-Set Cuing Inhibition in Category-Instance and Reason Generation. Bulletin of the Psychonomic Society 29 (2):136-138.
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