Paper
27 May 2005 A standard intelligent system ontology
Author Affiliations +
Abstract
The level of automation in combat vehicles being developed for the Army's objective force is greatly increased over the Army's legacy force. This automation is taking many forms in emerging vehicles; varying from operator decision aides to fully autonomous unmanned systems. The development of these intelligent vehicles requires a thorough understanding of all of the intelligent behavior that needs to be exhibited by the system so that designers can allocate functionality to humans and/or machines. Traditional system specification techniques focused heavily on the functional description of the major systems and implicitly assumed that a well-trained crew would operate these systems in a manner to accomplish the tactical mission assigned to the vehicle. In order to allocate some or all of these intelligent behaviors to machines in future vehicles it is necessary to be able to identify and describe these intelligent behaviors in detail. In this paper, we describe an effort to develop an intelligent systems (IS) ontology using Protege. The goal of this effort is to develop a common, implementation-independent, extendable knowledge source for researchers and developers in the intelligent vehicle community that will: * Provide a standard set of domain concepts along with their attributes and inter-relations * Allow for knowledge capture and reuse * Facilitate systems specification, design, and integration, and * Accelerate research in the field. This paper describes the methodology we have used to identify knowledge in this domain and an approach to capture and visualize the knowledge in the ontology.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Craig Schlenoff, Randy Washington, Tony Barbera, and Chris Manteuffel "A standard intelligent system ontology", Proc. SPIE 5804, Unmanned Ground Vehicle Technology VII, (27 May 2005); https://doi.org/10.1117/12.602425
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CITATIONS
Cited by 9 scholarly publications.
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KEYWORDS
Intelligence systems

Roads

Standards development

Navigation systems

Process modeling

Reconnaissance

Data modeling

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