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    Author(s): Donald Nute; Walter D. Potter; Mayukh Dass; Astrid Glende; Frederick Maier; Hajime Uchiyama; Jin Wang; Mark Twery; Peter Knopp; Scott Thomasma; H. Michael Rauscher
    Date: 2003
    Source: Decision Support for Multiple Purpose Forestry, April 23-25, Vienna, Austria, p. 1-11
    Publication Series: Scientific Journal (JRNL)
    PDF: Download Publication  (623 KB)


    A wide variety of software tools are available to support decision in the management of forest ecosystems. These tools include databases, growth and yield models, wildlife models, silvicultural expert systems, financial models, geographical informations systems, and visualization tools. Typically, each of these tools has its own complex interface and data format. To use these tools in combination, a manager must learn each interface and manually convert data from one format to another. NED-2 uses a blackboard architechture and a set of semi-autonomous agents to manage these tools for hte user. Each agent has the procedural knowledge needed to operate a class of decisions support tools used in forest ecosystem management. The simulation agent can set up input for growth and yield models and knows how to interpret the output from these models. Meta-knowledge bases provide the simulation agent with information about the data formats and control codes used by different growth simulators. The GIS agent can merge information with a shape file and knows how to invoke a geographical information system to display the information. The visualization agent can generate input for stand and landscape visualization tools. The blackboard systems itself includes a powerful agent that integrates a database and a set of Prolog clauses into a single blackboard. The interface agent provides access to all the tools in the system through a single user interface. Other agents allow development of alternative treatment plans; provide analysis of timber, wildlife, water, ecology, and visual goals; and generate a wide variety of reports useful in forest management. The agent architecture is designed to facilitate integration of new third-party decision support tools as they become available.

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    Nute, Donald; Potter, Walter D.; Dass, Mayukh; Glende, Astrid; Maier, Frederick; Uchiyama, Hajime; Wang, Jin; Twery, Mark; Knopp, Peter; Thomasma, Scott; Rauscher, H. Michael. 2003. An agent architecture for an integrated forest ecosystem management decision support system. Decision Support for Multiple Purpose Forestry, April 23-25, Vienna, Austria, p. 1-11


    Agent architecture, blackboard architecture, ecosystem management, model management, decision support system, knowledge based system, Prolog

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