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Development of Self-organising Emergent Applications with Simulation-Based Numerical Analysis

机译:基于仿真的数值分析的自组织新兴应用的开发

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The goal of engineering self-organising emergent systems is to acquire a macroscopic system behaviour solely from autonomous local activity and interaction. Due to the non-deterministic nature of such systems, it is hard to guarantee that the required macroscopic behaviour is achieved and maintained. Before even considering a self-organising emergent system in an industrial context, e.g. for Automated Guided Vehicle (AGV) transportation systems, such guarantees are needed. An empirical analysis approach is proposed that combines realistic agent-based simulations with existing scientific numerical algorithms for analysing the macroscopic behaviour. The numerical algorithm itself obtains the analysis results on the fly by steering and accelerating the simulation process according to the algorithm’s goal. The approach is feasible, compared to formal proofs, and leads to more reliable and valuable results, compared to mere observation of simulation results. Also, the approach allows to systematically analyse the macroscopic behaviour to acquire macroscopic guarantees and feedback that can be used by an engineering process to iteratively shape a self-organising emergent solution.
机译:工程自组织紧急系统的目标是仅从自主局部活动和互动中获取宏观系统行为。由于这种系统的非确定性性质,很难保证所需的宏观行为和维护。在甚至考虑在工业环境中的自组织紧急系统之前,例如对于自动引导车辆(AGV)运输系统,需要这样的保证。提出了一种经验分析方法,其将基于逼真的基于代理的模拟与现有的科学数值算法相结合,用于分析宏观行为。根据算法的目标,数值算法本身通过转向和加速模拟过程来获得分析结果。与正式证据相比,该方法是可行的,与Mere观察模拟结果的观察相比,导致更可靠和有价值的结果。此外,该方法允许系统地分析宏观行为以获取可以由工程过程使用的宏观保证和反馈来迭代地塑造自组织的紧急解决方案。

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