16 found
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  1.  7
    Alex Wiegmann & Michael R. Waldmann (2014). Transfer Effects Between Moral Dilemmas: A Causal Model Theory. Cognition 131 (1):28-43.
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  2.  11
    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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  3.  3
    Ralf Mayrhofer & Michael R. Waldmann (2015). Agents and Causes: Dispositional Intuitions As a Guide to Causal Structure. Cognitive Science 39 (1):65-95.
    Currently, two frameworks of causal reasoning compete: Whereas dependency theories focus on dependencies between causes and effects, dispositional theories model causation as an interaction between agents and patients endowed with intrinsic dispositions. One important finding providing a bridge between these two frameworks is that failures of causes to generate their effects tend to be differentially attributed to agents and patients regardless of their location on either the cause or the effect side. To model different types of error attribution, we augmented (...)
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  4. Michael R. Waldmann, Patricia W. Cheng, York Hagmeyer & Blaisdell & P. Aaron (2008). Causal Learning in Rats and Humans: A Minimal Rational Model. In Nick Chater & Mike Oaksford (eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science. OUP Oxford
     
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  5.  4
    Michael R. Waldmann, Keith J. Holyoak & Angela Fratianne (1995). Causal Models and the Acquisition of Category Structure. Journal of Experimental Psychology: General 124 (2):181.
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  6.  11
    Michael R. Waldmann & Alex Wiegmann (2010). A Double Causal Contrast Theory of Moral Intuitions in Trolley Dilemmas. In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society 2589--2594.
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  7.  5
    Michael R. Waldmann, Patricia W. Cheng, York Hagmayer & Aaron P. Blaisdell (2008). Causal Learning in Rats and Humans: A Minimal Rational Model. In Nick Chater & Mike Oaksford (eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science. OUP Oxford
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  8.  61
    Michael R. Waldmann (2011). Neurath's Ship: The Constitutive Relation Between Normative and Descriptive Theories of Rationality. Behavioral and Brain Sciences 34 (5):273-274.
    I defend the claim that in psychological theories concerned with theoretical or practical rationality there is a constitutive relation between normative and descriptive theories: Normative theories provide idealized descriptive accounts of rational agents. However, we need to resist the temptation to collapse descriptive theories with any specific normative theory. I show how a partial separation is possible.
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  9.  8
    Ralf Mayrhofer & Michael R. Waldmann (2015). Sufficiency and Necessity Assumptions in Causal Structure Induction. Cognitive Science 40 (4).
    Research on human causal induction has shown that people have general prior assumptions about causal strength and about how causes interact with the background. We propose that these prior assumptions about the parameters of causal systems do not only manifest themselves in estimations of causal strength or the selection of causes but also when deciding between alternative causal structures. In three experiments, we requested subjects to choose which of two observable variables was the cause and which the effect. We found (...)
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  10.  9
    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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  11.  2
    Michael R. Waldmann (2007). Combining Versus Analyzing Multiple Causes: How Domain Assumptions and Task Context Affect Integration Rules. Cognitive Science 31 (2):233-256.
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  12.  6
    Jonas Nagel & Michael R. Waldmann (2015). On Having Very Long Arms: How the Availability of Technological Means Affects Moral Cognition. Thinking and Reasoning 22 (2):184-208.
    ABSTRACTModern technological means allow for meaningful interaction across arbitrary distances, while human morality evolved in environments in which individuals needed to be spatially close in order to interact. We investigate how people integrate knowledge about modern technology with their ancestral moral dispositions to help relieve nearby suffering. Our first study establishes that spatial proximity between an agent's means of helping and the victims increases people's judgement of helping obligations, even if the agent is constantly far personally. We then report and (...)
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  13.  29
    York Hagmayer, Björn Meder, Momme von Sydow & Michael R. Waldmann (2011). Category Transfer in Sequential Causal Learning: The Unbroken Mechanism Hypothesis. Cognitive Science 35 (5):842-873.
    The goal of the present set of studies is to explore the boundary conditions of category transfer in causal learning. Previous research has shown that people are capable of inducing categories based on causal learning input, and they often transfer these categories to new causal learning tasks. However, occasionally learners abandon the learned categories and induce new ones. Whereas previously it has been argued that transfer is only observed with essentialist categories in which the hidden properties are causally relevant for (...)
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  14.  1
    Michael R. Waldmann & York Hagmayer (2001). Estimating Causal Strength: The Role of Structural Knowledge and Processing Effort. Cognition 82 (1):27-58.
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  15.  2
    Alex Wiegmann, Jana Samland & Michael R. Waldmann (2016). Lying Despite Telling the Truth. Cognition 150:37-42.
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  16.  2
    Ralf Mayrhofer & Michael R. Waldmann (2014). Indicators of Causal Agency in Physical Interactions: The Role of the Prior Context. Cognition 132 (3):485-490.
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