On Knowledge Amplification by Structured Expert Randomization (KASER)

Abstract

This paper defines Knowledge Amplification by Structured Expert Randomization (KASER). A KASER can automatically acquire a virtual rule space exponentially larger than the actual rule space and with an exponentially decreasing nonzero likelihood of error. The KASER cracks the knowledge acquisition bottleneck in intelligent systems by amplifying user-supplied knowledge. This enables the construction of an intelligent system, which is creative, fail-soft, learns over a network, and otherwise has enormous potential for automated decision making.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2001
Accession Number
ADA434118

Entities

People

  • Stuart H. Rubin

Organizations

  • Naval Information Warfare Systems Command

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Acquisition
  • Amplification
  • Command And Control
  • Computer Programming
  • Computer Programs
  • Computers
  • Data Acquisition
  • Databases
  • Expert Systems
  • Explosive Gases
  • Grammars
  • Graphical User Interface
  • Intelligent Systems
  • Jet Propulsion
  • Language
  • Lisp Programming Language

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Molecular Genetics
  • Regression Analysis.

Technology Areas

  • Space