Abstract
Cross-situational word learning is based on the notion that a learner can determine the referent of a word by finding something in common across many observed uses of that word. Here we propose an adaptive learning algorithm that contains a parameter that controls the strength of the reinforcement applied to associations between concurrent words and referents, and a parameter that regulates inference, which includes built-in biases, such as mutual exclusivity, and information of past learning events. By adjusting these parameters so that the model predictions agree with data from representative experiments on cross-situational word learning, we were able to explain the learning strategies adopted by the participants of those experiments in terms of a trade-off between reinforcement and inference. These strategies can vary wildly depending on the conditions of the experiments. For instance, for fast mapping experiments (i.e., the correct referent could, in principle, be inferred in a single observation) inference is prevalent, whereas for segregated contextual diversity experiments (i.e., the referents are separated in groups and are exhibited with members of their groups only) reinforcement is predominant. Other experiments are explained with more balanced doses of reinforcement and inference.
Highlights
A desirable goal of a psychological theory is to offer explanations grounded on elementary principles to the data available from psychology experiments (Newell, 1994)
In that sense, learning takes place through the statistical sampling of the contexts in which a word appears in accord with the classical associationist stance of Hume and Locke that the mechanism of word learning is sensitivity to covariation: if two events occur at the same time, they become associated (Bloom, 2000)
Different trials exhibiting distinct word-object pairs will eventually allow the disambiguation of the word-object associations and the learning of the correct mapping (Yu and Smith, 2007). It is questionable whether this scenario is suitable to describe the actual word learning process by children even in the unambiguous situation where the single novel object is followed by the utterance of its corresponding pseudo-word
Summary
A desirable goal of a psychological theory is to offer explanations grounded on elementary principles to the data available from psychology experiments (Newell, 1994) Most of these quantitative psychological data are related to mental chronometry and memory accuracy, recent explorations on the human performance to acquire an artificial lexicon in controlled laboratory conditions have paved the way to the understanding of the learning strategies humans use to infer a word-object mapping (Yu and Smith, 2007; Kachergis et al, 2009; Smith et al, 2011; Kachergis et al, 2012; Yu and Smith, 2012a). There have been claims that cross-situational statistical learning is part of the repertoire of young word learners (Yu and Smith, 2008), the effect of individual differences in attention and vocabulary development of the infants complicates considerably this issue which is still a matter for debate (Yu and Smith, 2012b; Smith and Yu, 2013)
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