Self-organised collective decision making is one of the core components of swarm intelligence, and numerous swarm algorithms that are widely used in optimisation and optimal control have been inspired by the biological mechanisms driving it. Beyond the life sciences and bio-inspired engineering, collective decision making is important in a number of other disciplines, most prominently economics and the social sciences. A paradigmatic model system for collective decision making is the foraging behaviour of mass recruiting ant colonies. While this system has been investigated extensively, our knowledge about its function in dynamic environments is still incomplete at best. We show that the mathematical model of mass foraging is really just a specific instance of a very general class of rational group decision making processes. We analyse this general class using an information-theoretic framework, which allows us to abstract from the specific details of a fixed model system. We specifically investigate how noisy communication can enable groups to share information about changes in an environment more efficiently. In the present paper, we show that an optimal noise level exists and that this optimal level depends on the rate of change in the environment. We explain this on the basis of stochastic resonance theory and show why stochastic attractor switching is a suitable base mechanism for adaptive group decision making in dynamic environments.

中文翻译：

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集体决策中的最优信息传递和随机共振

自组织的集体决策是群体智能的核心组成部分，而驱动其生物学机制启发了众多在优化和最优控制中广泛使用的群体算法。除了生命科学和生物工程学之外，集体决策在许多其他学科中也很重要，最主要的是经济学和社会科学。集体决策的范式模型系统是大规模招募蚁群的觅食行为。尽管对该系统进行了广泛的研究，但我们对其在动态环境中的功能的了解充其量仍是充斥的。我们表明，大规模觅食的数学模型实际上只是理性群体决策过程中非常通用的一类特定实例。我们使用信息理论框架来分析此通用类，该框架使我们能够从固定模型系统的特定细节中进行抽象。我们专门研究嘈杂的通信如何使团体更有效地共享有关环境变化的信息。在本文中，我们表明存在最佳噪声水平，并且该最佳水平取决于环境的变化率。我们根据随机共振理论对此进行解释，并说明为什么随机吸引子切换是动态环境中自适应群体决策的合适基础机制。我们专门研究嘈杂的通信如何使团体更有效地共享有关环境变化的信息。在本文中，我们表明存在最佳噪声水平，并且该最佳水平取决于环境的变化率。我们根据随机共振理论对此进行解释，并说明为什么随机吸引子切换是动态环境中自适应群体决策的合适基础机制。我们专门研究嘈杂的通信如何使团体更有效地共享有关环境变化的信息。在本文中，我们表明存在最佳噪声水平，并且该最佳水平取决于环境的变化率。我们根据随机共振理论对此进行解释，并说明为什么随机吸引子切换是动态环境中自适应群体决策的合适基础机制。