关于空间分布式代理计算加速：一种补丁动力学方案
On the acceleration of spatially distributed agent-based computations: a patch dynamics scheme
AI总结：
本文提出一种基于有限体积的保守补丁动力学方案，用于加速空间分布式代理计算，应用于金融市场代理模型，显示其在空间和时间上均显著降低计算成本。
摘要：
近年来，基于个体/代理的建模已被应用于从工程问题到社会科学、经济学和生物学现象的广泛领域。在扩展的时空域上模拟此类代理模型可能由于随机性和多尺度的存在而变得非常昂贵。然而，许多代理问题在宏观尺度上表现出空间和时间的平滑行为，表明可以得到有用的粗粒度连续模型。对于此类问题，方程无关框架[16-18]可以显著降低计算成本。补丁动力学是该框架的重要组成部分。该方案设计用于在宏观时间和长度尺度上进行不可用宏观方程的数值模拟；它使用在多个小
英文摘要：
In recent years, individual-based/agent-based modeling has been applied to study a wide range of applications, ranging from engineering problems to phenomena in sociology, economics and biology. Simulating such agent-based models over extended spatiotemporal domains can be prohibitively expensive due to stochasticity and the presence of multiple scales. Nevertheless, many agent-based problems exhibit smooth behavior in space and time on a macroscopic scale, suggesting that a useful coarse-grained continuum model could be obtained. For such problems, the equation-free framework [16-18] can significantly reduce the computational cost. Patch dynamics is an essential component of this framework. This scheme is designed to perform numerical simulations of an unavailable macroscopic equation on macroscopic time and length scales; it uses appropriately initialized simulations of the fine-scale agent-based model in a number of small "patches", which cover only a fraction of the spatiotemporal domain. In this work, we construct a finite-volume-inspired conservative patch dynamics scheme and apply it to a financial market agent-based model based on the work of Omurtag and Sirovich [22]. We first apply our patch dynamics scheme to a continuum approximation of the agent-based model, to study its performance and analyze its accuracy. We then apply the scheme to the agent-based model itself. Our computational experiments indicate that here, typically, the patch dynamics-based simulation requires only 20% of the full agent-based simulation in space, and need occur over only 10% of the temporal domain.
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