Multiagent Decision-Making Dynamics Inspired by Honeybees
Multiagent Decision-Making Dynamics Inspired by Honeybees
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DOI：
10.1109/tcns.2018.2796301
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发表时间：
2018-06-01
影响因子：
4.2
通讯作者：
Leonard, Naomi Ehrich
中科院分区：
文献类型：
--
作者：
Gray, Rebecca;Franci, Alessio;Leonard, Naomi Ehrich
当在候选筑巢地点之间进行选择时，蜂群会可靠地选择最有价值的地点，即使在价值接近相等的地点之间进行选择时，它也会做出高效的决策。价值敏感的决策是由蜜蜂之间的分布式社会努力实现的，它导致了群体的决策动态，对扰动具有显著的鲁棒性和适应性变化。为了探索并将这些特征推广到其他网络，我们设计了分布式多智能体网络动力学，它表现出干草叉分叉，在决策的生物模型中无处不在。利用非线性动力学工具，我们展示了设计的基于智能体的动态如何恢复蜜蜂的高性能价值敏感决策，并将动物群体决策机制的研究与多智能体网络系统的系统、生物激励控制紧密联系起来。我们进一步提出了一种分布式自适应分岔控制律，并证明了它是如何提高网络决策性能的。
When choosing between candidate nest sites, a honeybee swarm reliably chooses the most valuable site and even when faced with the choice between near-equal value sites, it makes highly efficient decisions. Value-sensitive decision-making is enabled by a distributed social effort among the honeybees, and it leads to decision-making dynamics of the swarm that are remarkably robust to perturbation and adaptive to change. To explore and generalize these features to other networks, we design distributed multiagent network dynamics that exhibit a pitchfork bifurcation, ubiquitous in biological models of decision-making. Using tools of nonlinear dynamics, we show how the designed agent-based dynamics recover the high performing value-sensitive decision-making of the honeybees and rigorously connect an investigation of mechanisms of animal group decision-making to systematic, bioinspired control of multiagent network systems. We further present a distributed adaptive bifurcation control law and prove how it enhances the network decision-making performance beyond that observed in swarms.