An innovative application from the DARPA knowledge bases programs: Rapid development of a course of action critiquer

  • Tecuci G
  • Boicu M
  • Bowman M
 et al. 
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Abstract

This article presents a learning agent shell and methodology for building knowledge bases and agents and their innovative application to the development of a critiquing agent for military courses of action, a challenge problem set by the Defense Advanced Research Projects Agency's High-Performance Knowledge Bases Program. The learning agent shell includes a general problem-solving engine and a general learning engine for a generic knowledge base structured into two main components: (1) an ontology that defines the concepts from an application domain and (2) a set of task-reduction rules expressed with these concepts. The development of the critiquing agent was done by importing ontological knowledge from CYC and teaching the agent how an expert performs the critiquing task. The learning agent shell, the methodology, and the developed critiquer were evaluated in several intensive studies, demonstrating good results.

Author-supplied keywords

  • artificial intelligence
  • knowledge based programs
  • knowledge based systems
  • learning systems
  • persona

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  • SCOPUS: 2-s2.0-0035364136
  • SGR: 0035364136
  • ISSN: 07384602
  • PUI: 32611109

Authors

  • Gheorghe Tecuci

  • Mihai Boicu

  • Michael Bowman

  • Dorin Marcu

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