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  1. Generative Inferences Based on Learned Relations.Dawn Chen, Hongjing Lu & Keith J. Holyoak - 2017 - Cognitive Science 41 (S5):1062-1092.
    A key property of relational representations is their generativity: From partial descriptions of relations between entities, additional inferences can be drawn about other entities. A major theoretical challenge is to demonstrate how the capacity to make generative inferences could arise as a result of learning relations from non-relational inputs. In the present paper, we show that a bottom-up model of relation learning, initially developed to discriminate between positive and negative examples of comparative relations, can be extended to make generative inferences. (...)
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  • Analytic Causal Knowledge for Constructing Useable Empirical Causal Knowledge: Two Experiments on Pre‐schoolers.Patricia W. Cheng, Catherine M. Sandhofer & Mimi Liljeholm - 2022 - Cognitive Science 46 (5):e13137.
    Cognitive Science, Volume 46, Issue 5, May 2022.
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  • The Oxford Handbook of Causal Reasoning.Michael Waldmann (ed.) - 2017 - Oxford, England: Oxford University Press.
    Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...)
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