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首页> 外文期刊>Parallel Algorithms and Applications >Directing chemotaxis-based spatial self-organisation via biased, random initial conditions
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Directing chemotaxis-based spatial self-organisation via biased, random initial conditions

机译:通过有偏的随机初始条件指导基于趋化性的空间自组织

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摘要

Inspired by the chemotaxis interaction of living cells, we have developed an agent-based approach for self-organising shape formation. Since all our simulations begin with a different uniform random configuration and our agents move stochastically, it has been observed that the self-organisation process may form two or more stable final configurations. These differing configurations may be characterised via statistical moments of the agents' locations. In order to direct the agents to robustly form one specific configuration, we generate biased initial conditions whose statistical moments are related to moments of the desired configuration. With this approach, we are able to successfully direct the aggregating swarms to produce a desired macroscopic shape, starting from randomised initial conditions with controlled statistical properties.
机译:受活细胞趋化性相互作用的启发,我们开发了一种基于代理的自组织形状形成方法。由于我们所有的模拟都是从不同的均匀随机配置开始的,并且我们的代理随机地移动,因此已经观察到自组织过程可能形成两个或更多个稳定的最终配置。这些不同的配置可以通过代理位置的统计时刻来表征。为了指导代理稳健地形成一种特定的配置,我们生成有偏差的初始条件,其初始状态的统计矩与所需配置的矩有关。通过这种方法,我们能够成功地引导聚集的群体产生所需的宏观形状,从具有受控统计特性的随机初始条件开始。

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