AGL StimSelect: Software for automated selection of stimuli for artificial grammar learning

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AGL StimSelect: software for automated selection of stimuli for artificial grammar learning.

Artificial grammar learning (AGL) is an experimental paradigm that has been used extensively incognitive research for many years to study implicit learning, associative learning, and generalization on the basis of either similarity or rules. Without computer assistance, it is virtually impossible to generate appropriate grammatical training stimuli along with grammatical or nongrammatical test ...

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An Entropy Model for Artificial Grammar Learning

A model is proposed to characterize the type of knowledge acquired in artificial grammar learning (AGL). In particular, Shannon entropy is employed to compute the complexity of different test items in an AGL task, relative to the training items. According to this model, the more predictable a test item is from the training items, the more likely it is that this item should be selected as compat...

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Artificial grammar learning

A grammar is a way of specifying how elements should be ordered. One sort of grammar is a finite state grammar, as illustrated in Figure 1. It contains a finite number of states, represented by circles, connected by arrows showing allowable transitions. A grammatical sequence or ‘string’ can be produced by entering the network and changing states until the network is exited. So, for example, ac...

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Theories of artificial grammar learning.

Artificial grammar learning (AGL) is one of the most commonly used paradigms for the study of implicit learning and the contrast between rules, similarity, and associative learning. Despite five decades of extensive research, however, a satisfactory theoretical consensus has not been forthcoming. Theoretical accounts of AGL are reviewed, together with relevant human experimental and neuroscienc...

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ژورنال

عنوان ژورنال: Behavior Research Methods

سال: 2008

ISSN: 1554-351X,1554-3528

DOI: 10.3758/brm.40.1.164