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A DATA FLOW IMPLEMENTATION OF AGENT-BASED DISTRIBUTED GRAPH SEARCH

机译:基于Agent的分布式图形搜索的数据流实现

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Biological ants organize themselves into forager groups that converge to shortest paths to and from food sources. This has motivated development of a large class of biologically inspired agent-based graph search techniques, called Ant Colony Optimization, to solve diverse combinatorial problems. Our approach to parallel graph search uses multiple ant agent populations distributed across processors and clustered computers to solve large-scale graph search problems. We discuss our implementation using the NIST Data Flow System II, and show good scalability of our parallel search algorithm.
机译:生物蚂蚁将自己组织成觅食者群体,它们汇聚成往返食物来源的最短路径。这激发了一大类受生物启发的基于智能体的图搜索技术(称为蚁群优化)的发展,以解决各种组合问题。我们的并行图搜索方法使用分布在处理器和群集计算机之间的多个蚂蚁代理种群来解决大规模图搜索问题。我们讨论了使用NIST数据流系统II的实现,并展示了并行搜索算法的良好可伸缩性。

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