A tunable algorithm for collective decision-making
A tunable algorithm for collective decision-making
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DOI：
10.1073/pnas.0604801103
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发表时间：
2006-10-24
影响因子：
11.1
通讯作者：
Sumpter, David J. T.
中科院分区：
文献类型：
--
作者：
Pratt, Stephen C.;Sumpter, David J. T.
复杂的生物系统越来越多地被理解为指导系统组件行为的算法和连接它们的信息路径。鲁棒算法，或那些允许系统在面对内部或外部扰动时保持其功能的算法受到了很大的关注。与此同时，环境的变化要求算法的多功能性，或者随着外部环境的变化而自适应地改变系统功能的能力。因此，系统生物学的一个重要目标是识别可以满足多种挑战的生物算法，而不是狭隘地针对特定问题。在这里，我们表明，移民殖民地的蚂蚁Temnothorax curvispinosus调整一个单一的决策算法的参数，以适应两个不同的问题：迅速放弃他们的旧巢在危机和审慎的选择最好的新家时，他们的旧巢仍然完好无损。该算法使用了一个逐步承诺计划和法定人数规则，以整合信息收集的众多个体蚂蚁访问几个候选家庭。通过改变它们搜索和接受这些候选者的速度，蚂蚁产生了一个自适应地强调速度或准确性的群体级响应。我们提出这样的一般，但可调的算法作为复杂系统的设计功能，每个算法提供优雅的解决方案，范围广泛的问题。
Complex biological systems are increasingly understood in terms of the algorithms that guide the behavior of system components and the information pathways that link them. Much attention has been given to robust algorithms, or those that allow a system to maintain its functions in the face of internal or external perturbations. At the same time, environmental variation imposes a complementary need for algorithm versatility, or the ability to alter system function adaptively as external circumstances change. An important goal of systems biology is thus the identification of biological algorithms that can meet multiple challenges rather than being narrowly specified to particular problems. Here we show that emigrating colonies of the ant Temnothorax curvispinosus tune the parameters of a single decision algorithm to respond adaptively to two distinct problems: rapid abandonment of their old nest in a crisis and deliberative selection of the best available new home when their old nest is still intact. The algorithm uses a stepwise commitment scheme and a quorum rule to integrate information gathered by numerous individual ants visiting several candidate homes. By varying the rates at which they search for and accept these candidates, the ants yield a colony-level response that adaptively emphasizes either speed or accuracy. We propose such general but tunable algorithms as a design feature of complex systems, each algorithm providing elegant solutions to a wide range of problems.