From Associative Learning to Language Structure
From Associative Learning to Language Structure
This chapter reviews sources of regularity in language, including maximizing (vs. probability matching) in decision making and positive feedback (rich-get-richer) loops within and between individuals. It argues that gradual learning can manifest itself in abrupt changes in behaviour, and languages can look somewhat regular and systematic in everyday use despite being represented as networks of competing associations. The chapter then reviews the kinds of structures found in language, distinguishing between syntagmatic structure (sequencing, serial order), schematic structure (form-meaning mappings, constructions) and paradigmatic structure, which is argued to be necessary only for learning morphological paradigms. Two controversial issues are discussed. First, it is argued that associations in language are ‘bidirectional by default’ in that an experienced language learner tries to form associations in both directions but may fail in doing so. Second, learning is argued to often proceed in the general-to-specific directions, especially at the level of cues (predictors) as opposed to outputs (behaviours).
Keywords: maximizing, probability matching, positive feedback, rich-get-richer, Zipf, constructions, morphology, morphological paradigms, general-to-specific
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