Rules and Maps in Connectionist Symbol Processing

Abstract

This report contains two papers to be presented at the Eleventh Annual Conference of the Cognitive Science Society. The first describes a simulation of chunking in a connectionist network. The network applies context-sensitive rewrite rules to strings of symbols as they flow through its input buffer. Chunking is implemented as a form of self-supervised learning using back-propagation. Over time, the network improves its efficiency by replacing simple rule sequences with more complex chunks. The second paper describes the first implementation of Lakoff's new theory of cognitive phonology. His approach is based on a multilevel representation of utterances to which all rules apply in parallel. Cognitive phonology is free of the rule ordering constraints that make classical generative theories computationally p awkward. The connectionist implementation utilizes a novel many maps architecture that may explain certain constraints on phonological rules not adequately accounted for by more abstract models. Keywords: Cognitive phonology; Linguistics; Many-maps model; Voice communication.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1989
Accession Number
ADA219028

Entities

People

  • David S. Touretzky

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Acquisition
  • Artificial Intelligence
  • Classification
  • Cognitive Science
  • Computer Programs
  • Computer Science
  • Computers
  • Contracts
  • Language
  • Linguistics
  • Military Research
  • Notation
  • Procurement
  • Psychology
  • Simulations
  • Universities

Readers

  • Computational Linguistics
  • Computer Networking
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation