Probabilistic learning algorithms and optimality theory
This article provides a critical assessment of the Gradual Learning Algorithm (GLA) for probabilistic optimality-theoretic (OT) grammars proposed by Boersma and Hayes (2001). We discuss the limitations of a standard algorithm for OT learning and outline how the GLA attempts to overcome these limitat...
| Huvudupphovsmän: | , |
|---|---|
| Materialtyp: | Journal article |
| Språk: | English |
| Publicerad: |
2002
|