Overcoming the Problem of Brittleness with the Metacognitive Loop

Abstract

The metacognitive loop (MCL) is architecture for automated noting, repairing, and learning from errors. Initial work on this award involved building special purpose MCL programs for each individual application domain Later in the award period a more uniform approach was designed that employs a general framework providing ontologies for types of Indications, Failures, and Repairs. This allows the past results in different domains to be achievable by a single MCL module, changing only the domain and the IFR ontologies. As a consequence, the investigators are now positioned (starting in 2009, with a new award) to begin to build a general-purpose MCL module that, when "attached" to a given host program H and an initial set of IFR ontologies, can adapt to the domain that H lives in (and in the process adapt the ontologies to better fit that domain) so that H+MCL guides itself to become less brittle.

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Document Details

Document Type
Technical Report
Publication Date
Nov 30, 2008
Accession Number
ADA586716

Entities

People

  • Donald Perlis
  • Michael Anderson
  • Tim Oates

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Autonomy
  • Human Systems
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Acquisition
  • Artificial Intelligence
  • Autonomous Systems
  • Brittleness
  • Classification
  • Department Of Defense
  • Information Operations
  • Intelligent Systems
  • Language
  • Learning
  • Models
  • Natural Languages
  • Ontologies
  • Reasoning
  • Students
  • Universities

Readers

  • Artificial Intelligence
  • Oncology
  • Systems Analysis and Design