多分辨多智能体仿真中智能体状态估计方法

Dariusz Pierzchala, Przemyslaw Czuba
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引用次数: 1

摘要

在多分辨多智能体仿真中,提出了多智能体状态逼近技术。我们使用的状态聚合和解聚的关键方法是:共识算法和编队控制。多主体协调的思想是从对生物实体集体行为的观察和模拟中产生的。共识算法是解决多智能体系统协同控制问题的常用算法,而编队控制是多智能体系统中最流行和最基本的运动协调问题,其中智能体收敛到预定的几何形状。该方法表明,多智能体方法在多分辨率仿真中具有广阔的应用前景。共识和群体控制算法消除了为聚合和分解需求指定复杂得多的算法的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Method of agents’ state estimation in multiresolution multiagent simulation
The paper proposes the multiagent techniques for approximation of agent’s state in the multiresolution multiagent simulation. The key methods we have used for state aggregation and disaggregation are: consensus algorithm and formation control. The idea of the coordination of multiple agents has emerged from both observation and simulation of a collective behavior of biological entities. The consensus algorithms are commonly used for the cooperative control problems in the multiagent systems, whilst the formation control is the most popular and fundamental motion coordination problem in the multiagent systems, where agents converge to predefined geometric shapes. The presented approach shows that multiagent methods seem to be very promising in multiresolution simulation. Consensus and formation control algorithms remove necessity to specify the much more complex algorithms for the aggregation and disaggregation needs.
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