Optimization and Quantization in Gradient Symbol Systems: A Framework for Integrating the Continuous and the Discrete in Cognition

@article{Smolensky2014OptimizationAQ,
  title={Optimization and Quantization in Gradient Symbol Systems: A Framework for Integrating the Continuous and the Discrete in Cognition},
  author={Paul Smolensky and Matthew Goldrick and Donald Mathis},
  journal={Cognitive science},
  year={2014},
  volume={38 6},
  pages={1102-38}
}
Mental representations have continuous as well as discrete, combinatorial properties. For example, while predominantly discrete, phonological representations also vary continuously; this is reflected by gradient effects in instrumental studies of speech production. Can an integrated theoretical framework address both aspects of structure? The framework we introduce here, Gradient Symbol Processing, characterizes the emergence of grammatical macrostructure from the Parallel Distributed… CONTINUE READING
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