Continually Plastic Modeling of Non-Stationary Systems

Abstract

This award supported extensions to, and novel applications of, an increasingly useful machine learning methodology known as symbolic regression. The PI of this award was involved in earlier work that established this approach as a powerful method for discovering previously unknown relationships within and among arbitrary data sets.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2016
Accession Number
AD1017264

Entities

People

  • Christopher M Danforth
  • Josh Bongard

Organizations

  • University of Vermont

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Ground and Sea Platforms
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cognition
  • Cognitive Science
  • Computational Science
  • Data Mining
  • Data Science
  • Drainage Basins
  • Geography
  • Information Processing
  • Information Science
  • Machine Learning
  • Network Science
  • Predictive Modeling
  • Psychology
  • Surveys
  • Two Dimensional
  • Wireless Sensor Networks

Readers

  • Mathematical Modeling and Probability Theory.
  • Regression Analysis.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks