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Similar neural correlates for language and sequential learning: Evidence from event-related brain potentials
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In: http://cnl.psych.cornell.edu/pubs/2012-cco-LCP.pdf (2012)
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Toward a New Scientific Visualization for the Language Sciences
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In: Information ; Volume 3 ; Issue 1 ; Pages 124-150 (2012)
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An empirical generative framework for computational modeling of language acquisition
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In: http://www.wisdom.weizmann.ac.il/%7Eedelman/Waterfall-Sandbank-Onnis-Edelman-JCL10.pdf (2010)
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Lexical categories at the edge of the word
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In: http://www2.hawaii.edu/~lucao/papers/OnnisChristiansen2008.pdf (2008)
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1Variability is an important ingredient in learning
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In: http://bcl.wjh.harvard.edu/images/uploaded/File/Onnisetal-variability.pdf (2006)
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New beginnings and happy endings: Psychological plausibility in computational models of language acquisition
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In: http://csjarchive.cogsci.rpi.edu/Proceedings/2005/docs/p1678.pdf (2005)
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New beginnings and happy endings: Psychological plausibility in computational models of language acquisition
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In: http://www.psych.unito.it/csc/cogsci05/frame/talk/p807-onnis.pdf (2005)
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New beginnings and happy endings: Psychological plausibility in computational models of language acquisition
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In: http://cnl.psych.cornell.edu/pubs/2005-oc-CogSci.pdf (2005)
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Corresponding author:
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In: http://www.cstr.ed.ac.uk/downloads/publications/2005/jml.pdf (2005)
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Variability is the spice of learning, and a crucial ingredient for detecting and generalizing in nonadjacent dependencies
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In: http://cnl.psych.cornell.edu/pubs/2004-OMCC-cogsci.pdf (2004)
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Reduction of uncertainty in human sequential learning: evidence from artificial language learning
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In: http://www.dectech.co.uk/publications/LinksNick/Language/Reduction of Uncertainty in Human Sequential Learning Eviden.pdf (2003)
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Using Phoneme Distributions to Discover Words and Lexical Categories in Unsegmented Speech
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In: http://cnl.psych.cornell.edu/pubs/2006-cho-cogsci.pdf
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lexical categories
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In: http://cnl.psych.cornell.edu/pubs/2009-coh-Dev-Science.pdf
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1 Language-induced Biases on Human Sequential Learning
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In: http://mindmodeling.org/cogsci2012/papers/0150/paper0150.pdf
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1 Acquisition and Evolution of Natural Language 134 Acquisition and Evolution of quasi-regular languages: Two puzzles for the price of one. Abstract
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In: http://cnl.psych.cornell.edu/papers/Roberts_Onnis_Chater.pdf
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References words: 843 Total words: 1,949 The Bottleneck May Be the Solution, Not the Problem
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In: http://kybele.psych.cornell.edu/%7Eedelman/Archive/Lotem-et-al-on-Christiansen-and-Chater-resubmitted.pdf
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Abstract:
Abstract. As a highly consequential biological trait, a memory “bottleneck ” cannot escape selection pres-sures. It must therefore co-evolve with other cognitive mechanisms rather than act as an inde-pendent constraint. Recent theory and an implemented model of language acquisition suggest that a limit on working memory may evolve to help learning. Furthermore, it need not hamper the use of language for communication. The target paper by Christiansen and Chater (C&C) makes many useful and valid observations about lan-guage that we happily endorse. Indeed, several of C&C’s major points appear in our own papers, including: (i) the inability of non-chunked, “analog ” approaches to language to compete with “digital ” combinatorics over chunks (Edelman, 2008b); (ii) the centrality of chunking to modeling incremental, memory-constrained language acquisition and generation (Goldstein et al., 2010; Kolodny et al., 2015b) and the possible evolu-tionary roots of these features of language (Lotem and Halpern, 2012; Kolodny et al., 2014, 2015a); (iii) the realization that language experience has the form of a graph (Solan et al., 2005; cf. Edelman, 2008a, 1 p.274), corresponding to C&C’s “forest tracks ” analogy; (iv) a proposed set of general principles for lan-
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.698.5467 http://kybele.psych.cornell.edu/%7Eedelman/Archive/Lotem-et-al-on-Christiansen-and-Chater-resubmitted.pdf
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Variation Sets Facilitate Artificial Language Learning
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In: http://www.wisdom.weizmann.ac.il/~edelman/OnnisWaterfallEdelman-variation-sets-CogSci08.pdf
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Variation Sets Facilitate Artificial Language Learning
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In: http://csjarchive.cogsci.rpi.edu/Proceedings/2008/pdfs/p1011.pdf
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