Predicting nearest agent distances in artificial worlds.
Predicting nearest agent distances in artificial worlds.
复制标题
预测人工世界中最近的代理距离。
DOI：
10.1162/106454602320991846
复制
发表时间：
2002
期刊：
影响因子：
--
通讯作者：
Reggia,JamesA
中科院分区：
文献类型：
--
作者：
Schulz,ReinerA;Reggia,JamesA
在许多多智能体人工生命研究中，智能体在有限的距离内相互作用，特定行为的出现和/或演变可能严重依赖于智能体间的距离。关于如何预测这样的距离，以前很少有理论分析。在本文中，我们推导出一个概率方法，在一个任意位置的代理在一个二维细胞世界，预测预期的距离最近的其他代理。我们的方法适用于许多世界拓扑结构，我们将其应用于确定六种常用拓扑结构的预期距离。此外，该方法易于适应于处理特殊限制。在各种各样的代理密度，我们表明，理论上预测的距离在很大程度上与随机放置的代理在计算实验中测得的距离一致。然后，我们利用我们的预测方法来解释最近的观察，一个不精确的阈值存在的代理密度的演变的通信。因此，我们说明，尽管它的概念简单，我们的方法可以帮助分析，甚至设计复杂的人工环境填充代理有可能相互作用。
In a number of multi-agent artificial life studies where agents interact over limited distances, the emergence and/or evolution of a specific behavior may depend critically upon interagent distances. Little theoretical analysis has been done previously concerning how to predict such distances. In this paper, we derive a probabilistic method that, for an agent at an arbitrary location in a two-dimensional cellular world, predicts the expected distance to a nearest other agent. Our method works for many world topologies, and we apply it to determine the expected distance for six commonly used ones. Further, the method is readily adapted to handle special restrictions. Over a wide variety of agent densities we show that the theoretically predicted distances are largely in agreement with the distances measured in computational experiments with randomly placed agents. We then utilize our prediction method to interpret recent observations that an imprecise threshold in the density of agents exists for the evolution of communication. We thus illustrate that, despite its conceptual simplicity, our method can aid the analysis and even the design of complex artificial environments populated by agents that have the potential to interact with one another.