Maximizing the Benefits of Training by Example and Direct Instruction

Abstract

One major accomplishment in this project was the development of the CLUSTer Error Reduction (CLUSTER) model's formalism. The updated equations can be downloaded at http://love.psy.utexas.edu/~love/cluster.pdf. One popular approach to modeling human category learning in the face of challenging data has been to propose models containing multiple systems. These systems could include prototype, exemplar, or rule-based components, as well as gating mechanisms that determine how to combine the outputs from these systems or components. CLUSTER takes a complex systems approach in which "systems" emerge out of the learners interactions with their environment. One claim is that what appears as separate cognitive systems are all based on cluster representations that follow from CLUSTER's recruitment and learning rules.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 08, 2008
Accession Number
ADA475484

Entities

People

  • Bradley C. Love

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force Personnel
  • Artificial Intelligence
  • Brain
  • Cognitive Neuroscience
  • Cognitive Science
  • Complex Systems
  • Environment
  • Instructions
  • Learning
  • Models
  • Neurosciences
  • Psychology
  • Reinforcement Learning
  • Students
  • Systems Approach
  • Training

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Parallel and Distributed Computing.
  • Systems Analysis and Design