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NED-2: an agent-based decision support system for forest ecosystem management

机译:NED-2:基于代理的森林生态系统管理决策支持系统

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摘要

Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard architecture and a set of semi-autonomous agents to manage these tools for the user. The blackboard integrates a Microsoft Access database and Prolog clauses, and the agents are implemented in Prolog. A graphical user interface written in Visual C++ provides powerful inventory analysis tools, dialogs for selecting timber, water, ecological, wildlife, and visual goals, and dialogs for defining treatments and building prescriptive management plans. Users can simulate management plans and perform goal analysis on different views of the management unit, where a view is determined by a management plan and a point in time. Prolog agents use growth and yield models to simulate management plans, perform goal analyses on user-specified views of the management unit, display results of plan simulation using GIS tools, and generate hypertext documents containing the results of such analysis. Individual agents use metaknowledge to set up and run external simulation models, to load rule-based models and perform inference, to set up and execute external GIS and visualization systems, and to generate hypertext reports as needed, relieving the user from performing all these tasks.
机译:森林生态系统管理的决策可以包括使用多种建模工具。这些工具包括植被生长模型,野生动物模型,造林模型,GIS和可视化工具。 NED-2是一个功能强大,智能,目标驱动的决策支持系统,该系统集成了每个类别中的工具。 NED-2使用黑板体系结构和一组半自治代理为用户管理这些工具。黑板集成了Microsoft Access数据库和Prolog子句,并且代理在Prolog中实现。用Visual C ++编写的图形用户界面提供了功能强大的清单分析工具,用于选择木材,水,生态,野生动植物和视觉目标的对话框,以及用于定义处理方法和制定规范性管理计划的对话框。用户可以在管理单元的不同视图上模拟管理计划并执行目标分析,其中视图由管理计划和时间点确定。 Prolog代理使用增长和收益模型来模拟管理计划,在管理单元的用户指定视图上执行目标分析,使用GIS工具显示计划模拟的结果以及生成包含此类分析结果的超文本文档。各个代理使用元知识来设置和运行外部仿真模型,加载基于规则的模型并执行推理,设置和执行外部GIS和可视化系统以及根据需要生成超文本报告,从而使用户不必执行所有这些任务。

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