A method for integrating multiple components in a decision support system

Donald Nute, Walter D. Potter, Zhiyuan Cheng, Mayukh Dass, Astrid Glende, Frederick Maierv, Cy Routh, Hajime Uchiyama, Jin Wang, Sarah Witzig, Mark Twery, Peter Knopp, Scott Thomasma, H. Michael Rauscher

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

We present a flexible, extensible method for integrating multiple tools into a single large decision support system (DSS) using a forest ecosystem management DSS (NED-2) as an example. In our approach, a rich ontology for the target domain is developed and implemented in the internal data model for the DSS. Semi-autonomous agents control external components and communicate using a blackboard. We illustrate how this multi-agent approach with its blackboard architecture supports the expansion of a DSS (in this case, NED-2) to incorporate new models and decision support tools as they become available. The exemplar NED-2 DSS developed using this method is a goal-driven DSS that integrates a sophisticated inventory system, treatment plan development, growth-and-yield models, wildlife models, fire risk models, knowledge based systems for goal satisfaction analysis, and a powerful report generation system.

Original languageEnglish
Pages (from-to)44-59
Number of pages16
JournalComputers and Electronics in Agriculture
Volume49
Issue number1
DOIs
StatePublished - Oct 2005

Keywords

  • Agents
  • Blackboard architecture
  • Decision support system
  • Ecosystem management
  • Fire risk analysis
  • Knowledge based system
  • Regeneration

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