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A Probabilistic Model of Early Argument Structure Acquisition
, 2008
"... Developing computational algorithms that capture the complex structure of natural language is an open problem. In particular, learning the abstract properties of language only from usage data remains a challenge. In this dissertation, we present a probabilistic usage-based model of verb argument str ..."
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Cited by 13 (3 self)
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Developing computational algorithms that capture the complex structure of natural language is an open problem. In particular, learning the abstract properties of language only from usage data remains a challenge. In this dissertation, we present a probabilistic usage-based model of verb argument structure acquisition that can successfully learn abstract knowledge of language from instances of verb usage, and use this knowledge in various language tasks. The model demonstrates the feasibility of a usage-based account of language learning, and provides concrete explanation for the observed patterns in child language acquisition. We propose a novel representation for the general constructions of language as probabilistic associations between syntactic and semantic features of a verb usage; these associations generalize over the syntactic patterns and the fine-grained semantics of both the verb and its arguments. The probabilistic nature of argument structure constructions in the model enables it to capture both statistical effects in language learning, and adaptability in language use. The acquisition of constructions is modeled as detecting similar usages and grouping them together. We use a probabilistic measure of similarity between
Item-based constructions and the logical problem
- ACL
, 2005
"... The logical problem of language is grounded on arguments from poverty of positive evidence and arguments from poverty of negative evidence. Careful analysis of child language corpora shows that, if one assumes that children learn through item-based constructions, there is an abundance of positive ev ..."
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Cited by 12 (4 self)
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The logical problem of language is grounded on arguments from poverty of positive evidence and arguments from poverty of negative evidence. Careful analysis of child language corpora shows that, if one assumes that children learn through item-based constructions, there is an abundance of positive evidence. Arguments regarding the poverty of negative evidence can also be addressed by the mechanism of conservative item-based learning. When conservativism is abandoned, children can rely on competition, cue construction,
2006 ). How computational models help explain the origins of reasoning
- 3 ), 32 – 40
"... Abstract: Developmental psychology is ready to blossom into a modern science that focuses on causal mechanistic explanations of development rather than just describing and classifying the skills that children show at different ages. Computational models of cognitive development are formal systems th ..."
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Cited by 6 (1 self)
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Abstract: Developmental psychology is ready to blossom into a modern science that focuses on causal mechanistic explanations of development rather than just describing and classifying the skills that children show at different ages. Computational models of cognitive development are formal systems that track the changes in information processing taking place as a behavior is acquired. Models are generally implemented as psychologically constrained computer simulations that learn tasks such as reasoning, categorization, and language. Their principal use is as tools for exploring mechanisms of transition (development) from one level of competence to the next during the course of cognitive development. They have been used to probe questions such as the extent of ‘pre-programmed ’ or innate knowledge that exists in the infant mind, and how the sophistication of reasoning can increase with age and experience. I. Understanding the
A Survey on Computational Models for Argument Structure Acquisition
, 2005
"... 2.1 Overgeneralization patterns.......................... 4 ..."
Item-based Constructions and the . . .
- PROCEEDINGS OF THE SECOND WORKSHOP ON PSYCHOCOMPUTATIONAL MODELS OF HUMAN LANGUAGE ACQUISITION, ANN ARBOR
, 2005
"... The logical problem of language is grounded on arguments from poverty of positive evidence and arguments from poverty of negative evidence. ..."
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The logical problem of language is grounded on arguments from poverty of positive evidence and arguments from poverty of negative evidence.
1 What are developmental psychologists looking for from a computational model?
"... Developmental psychology is ready to blossom into a modern science that focuses on causal mechanistic explanations of development rather than just describing and classifying behaviours. Computational modelling is the key to this process. However, to be effective models must not only mimic observed d ..."
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Developmental psychology is ready to blossom into a modern science that focuses on causal mechanistic explanations of development rather than just describing and classifying behaviours. Computational modelling is the key to this process. However, to be effective models must not only mimic observed data. They must also be transparent, grounded and plausible to be accepted by the developmental psychology community. Connectionist model provide one such example. Many developmental features of typical and atypical perception, cognition, and language have been modelled using connectionist methods. Successful models are closely tied to the details of existing empirical studies and make concrete testable predictions. The success of such a project relies on the close collaboration of computational scientists with empirical psychologists. 3 1.
