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Noise Reduction by Swarming in Social Foraging

机译：通过在社交觅食中群策群力减少噪音

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摘要

Swarms, flocks, and other group formations can be found in nature in many organisms ranging from simple bacteria to mammals. Such collective and coordinated behavior is effective for avoiding predators and/or for increasing the chances of finding food (foraging). In this technical note we develop a mathematical model for analyzing the benefits of social foraging in a noisy environment. We identify conditions on the nutrient profile ensuring that local agent actions will lead to cohesive foraging. For convex, smooth nutrient profiles, we formalize the way in which swarming for social foraging is better at handling the effects of noise when compared to the average of individual foraging strategies. Under a swarming discipline, observational noise realizations that induce trajectories differing too much from the group average are likely to be discarded because of each individual's need to maintain cohesion. As a result, the group trajectories are less affected by noise. Simulation experiments indicate our theoretical results are robust to inter-agent communication constraints and non-convex nutrient profiles. These results suggest that swarming-like approaches for the control of networked agents may provide an additional level of robustness.
机译：在自然界中，从简单细菌到哺乳动物的许多生物中都可以发现群，群和其他族群的形成。这种集体和协调的行为对于避免掠食者和/或增加寻找食物（觅食）的机会是有效的。在本技术说明中，我们建立了一个数学模型来分析嘈杂环境中社会觅食的好处。我们在营养素分布图上确定条件，以确保局部制剂的作用会导致内聚性觅食。对于凸面，光滑的营养状况，我们将群体觅食的方式正式化，使其与个体觅食策略的平均值相比，能够更好地处理噪声的影响。在拥挤的纪律下，由于每个人都需要保持凝聚力，导致轨迹偏离组平均值的观测噪声可能会被丢弃。结果，组轨迹受噪声影响较小。仿真实验表明，我们的理论结果对代理间的通信约束和非凸型营养素特征均具有较强的鲁棒性。这些结果表明，用于控制网络代理的群集方法可能会提供更高级别的鲁棒性。

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