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Annals of Compositional Rule of Inference and Adaptive Fuzzy Rule Based Scheme with Applications
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In: http://www.researchmathsci.org/apamart/apam-v3n2-7.pdf (2013)
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| 2 |
What is implicit causality?
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In: http://www.gameswithwords.org/Hartshorne/papers/Hartshorne_LCP_WhatIsIC.pdf (2013)
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Assessing presumptions in argumentation: Being a sound presumption vs. being presumably the case
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In: http://scholar.uwindsor.ca/cgi/viewcontent.cgi?article%3D1992%26context%3Dossaarchive (2013)
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| 4 |
Document and corpus level inference for unsupervised and transductive learning of information structure of scientic documents
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In: http://aclweb.org/anthology/C/C12/C12-2097.pdf (2012)
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| 5 |
a Grupo de Procesamiento de Lenguaje Natural
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In: http://hal.inria.fr/docs/00/53/66/33/PDF/preprint_jda.pdf (2012)
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| 6 |
Video Audio Interface for Recognizing Gestures of Indian Sign Language
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| 7 |
Effects of ignorance and information on judgments and decisions
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In: http://www.decisionsciencenews.com/sjdm/journal.sjdm.org/11/rh7/rh7.pdf (2011)
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| 8 |
The recognition heuristic: A decade of research
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In: http://www.decisionsciencenews.com/sjdm/journal.sjdm.org/11/rh15/rh15.pdf (2011)
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| 9 |
The recognition heuristic: A decade of research
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In: http://www.dangoldstein.com/papers/Gigerenzer_Goldstein_Recognition_Heuristic_Decade_JDM2011.pdf (2011)
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| 10 |
Semi-supervised learning with measure propagation
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In: http://jmlr.org/papers/volume12/subramanya11a/subramanya11a.pdf (2011)
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| 11 |
Parallels and differences in the treatment of metaphor in relevance theory and cognitive linguistics
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In: http://www.ucl.ac.uk/psychlangsci/research/linguistics/publications/wpl/10papers/Wilson2010/ (2010)
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| 12 |
Learning Long-Distance Phonotactics
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In: http://phonology.cogsci.udel.edu/%7Eheinz/papers/Heinz-2010-LLP.pdf (2010)
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| 13 |
Learning Long-Distance Phonotactics
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In: http://phonology.cogsci.udel.edu/%7Eheinz/papers/Heinz-2010-LLP.pdf (2010)
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| 14 |
Measuring Universal Intelligence: Towards an Anytime Intelligence Test
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In: http://users.dsic.upv.es/proy/anynt/measuring.pdf (2010)
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| 15 |
A one-toone bias and fast mapping support preschoolers learning about faces and voices
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In: http://www.psy.jhu.edu/%7Ehalberda/publications/cogs_1109_Feigenson.pdf (2010)
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| 16 |
Using contextual representations to efficiently learn context-free languages
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In: http://hal.archives-ouvertes.fr/docs/00/60/70/98/PDF/Learning_CBFG.pdf (2010)
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| 17 |
Using Contextual Representations to Efficiently Learn Context-Free Languages
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In: http://www.cs.rhul.ac.uk/home/alexc/papers/clark10a.pdf (2010)
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| 18 |
Covariance in unsupervised learning of probabilistic grammars
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In: http://www.cs.cmu.edu/%7Escohen/jmlr10pgcovariance.pdf (2010)
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| 19 |
Analogical and category-based inference: A theoretical integration with Bayesian causal models
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In: http://reasoninglab.psych.ucla.edu/wp-content/uploads/2010/09/Holyoak_Lee_Lu_2010.pdf (2010)
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Abstract:
A fundamental issue for theories of human induction is to specify constraints on potential inferences. For inferences based on shared category membership, an analogy, and/or a relational schema, it appears that the basic goal of induction is to make accurate and goal-relevant inferences that are sensitive to uncertainty. People can use source information at various levels of abstraction (including both specific instances and more general categories), coupled with prior causal knowledge, to build a causal model for a target situation, which in turn constrains inferences about the target. We propose a computational theory in the framework of Bayesian inference and test its predictions (parameter-free for the cases we consider) in a series of experiments in which people were asked to assess the probabilities of various causal predictions and attributions about a target on the basis of source knowledge about generative and preventive causes. The theory proved successful in accounting for systematic patterns of judgments about interrelated types of causal inferences, including evidence that analogical inferences are partially dissociable from overall mapping quality.
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Keyword:
analogical inference; Bayesian theory; category-based inference; causal models; schemas
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URL: http://reasoninglab.psych.ucla.edu/wp-content/uploads/2010/09/Holyoak_Lee_Lu_2010.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.665.3165
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| 20 |
An Intelligent System Visualization for Intelligence of Learners
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In: http://ijrte.academypublisher.com/vol01/no01/ijrte0101001005.pdf (2009)
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