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- W2025998974 abstract "Intelligent agents have successfully solved the train pathing problem on a small portion of railroad network [Tsen, 1995, Ph.D. Thesis, Carnegie Mellon University, USA]. As the railroad network grows, it is imperative that the agents collaborate to operate as efficiently as possible. In this paper, the authors demonstrate a collaboration protocol based on a conditional measure of agent effectiveness. Because agent effectiveness is not directly measurable, a suitable metric for agent effectiveness is introduced. Where typically agents run with uniform frequency, the collaboration protocol schedules the agents with a frequency proportional to their expected effectiveness. This protocol introduced a 10-fold improvement in the agent efficiency when tested with a simulation program on a portion of the Burlington Northern railroad." @default.
- W2025998974 created "2016-06-24" @default.
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- W2025998974 date "2002-12-01" @default.
- W2025998974 modified "2023-10-16" @default.
- W2025998974 title "Enhancing intelligent agent collaboration for flow optimization of railroad traffic" @default.
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- W2025998974 doi "https://doi.org/10.1016/s0965-8564(02)00002-2" @default.
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