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首页> 外文期刊>Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies >EKEMAS, an agent-based geo-simulation framework to support continual planning in the real-word
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EKEMAS, an agent-based geo-simulation framework to support continual planning in the real-word

机译:EKEMAS,一个基于代理的地理模拟框架,可支持真实单词的连续计划

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In this paper, we propose an agent-based geo-simulation framework EKEMAS to assist human planners when planning under strong spatial constraints in a real large-scale space. The approach consists in drawing a parallel between the real environment (for example, a forest in fire) and the simulated environment based on GIS data. This virtual environment uses software agents which are aware of the space and equipped with advanced spatial reasoning capabilities. In addition, we suggest some enhancements for the Continual Planning approach. Our aim is to demonstrate how EKEMAS, when coupled with a continual planning approach and agent's spatial reasoning capabilities, can assist human planners overcoming obstacles related to real world constraints: dynamic, uncertain, and spatially constrained environment. We illustrate this idea on the forest firefighting problem and we use MAGS as a simulation platform and Prometheus as a fire simulator. Finally, and since plans in the studied case (wildfire fighting) are mainly paths, we also propose a new approach based on agent geo-simulation in order to solve particular Pathfinding problems.
机译:在本文中,我们提出了一种基于代理的地理模拟框架EKEMAS,以帮助人类规划人员在实际的大型空间中强大的空间约束下进行规划时。该方法包括绘制真实环境(例如,火灾中的森林)与基于GIS数据的模拟环境之间的相似之处。该虚拟环境使用软件代理,这些代理了解空间并配备了高级空间推理功能。另外,我们建议对持续计划方法进行一些增强。我们的目的是演示EKEMAS,结合持续的规划方法和代理的空间推理能力,如何帮助人类规划人员克服与现实世界约束相关的障碍:动态,不确定和空间受限的环境。我们说明了有关森林消防问题的想法,并使用MAGS作为模拟平台,并使用Prometheus作为消防模拟器。最后,由于研究案例(野火扑救)中的计划主要是路径,因此我们还提出了一种基于代理地理模拟的新方法,以解决特定的寻路问题。

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