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Demo Paper: AGADE Scalability of Ontology Based Agent Simulations

机译:演示文件:基于本体的Agent仿真的AGADE可扩展性

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摘要

Simulations of real world scenarios often require considerably large numbers of agents. With increasing level of detail and resolution in the underlying models machine limitations both in the aspect of memory and computing power are reached. Even more when additional features like reasoning mechanisms of semantic technologies are used as in the AGADE framework where we have extended the principal BDI paradigm with an interface to OWL ontologies. We have observed that the extensive use of ontologies results in high memory consumption due to the large number of String objects used in the reasoning process and caching mechanisms of the OWL API. We address this issue by running simulations in a highly distributed environment. In this paper we demonstrate how we enabled AGADE to be run in such an environment and the necessary architectural modifications. Furthermore, we discuss the potential size of simulations that can be run in such a setting.
机译:真实世界场景的模拟通常需要大量的代理。随着底层模型中详细程度和分辨率的提高,机器在内存和计算能力方面均受到限制。当像AGADE框架中那样使用诸如语义技术的推理机制之类的附加功能时,甚至更多,我们在AADE框架中通过与OWL本体的接口扩展了主要BDI范例。我们已经观察到,由于在OWL API的推理过程和缓存机制中使用了大量String对象,因此本体的广泛使用导致高内存消耗。我们通过在高度分布式的环境中运行仿真来解决此问题。在本文中,我们演示了如何使AGADE在这样的环境中运行以及必要的体系结构修改。此外,我们讨论了可以在这种环境下运行的模拟的潜在规模。

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