BCSP: The Emergence of Inactivity: Adaptive Task Allocation in Complex Distributed Systems, or Why Are There so Many Lazy Ants?

生物学中最重要、也可能是最大的悬而未决的问题之一是，一组相对简单的部分如何形成组织有序、有效且往往美丽的结构。这发生在生命的起源中，分子簇形成细胞；发育中，最初未特化的细胞形成胚胎；以及许多其他系统，包括昆虫群体，小昆虫的聚集产生了适应性的群体行为。同样的现象也会更直接地影响人类，计算机集群、电网和组织中的人都会表现出不可预见的群体级别行为。这个项目专门调查这些小组中的各个单位可能用来划分任务的行为规则。分工在许多集体制度中扮演着重要的角色，对如何最好地实现这一目标缺乏系统的理解。该项目将为动物行为学、计算机科学和工程学领域做出实质性贡献。蚂蚁将被用作一个实证研究系统，并将开发数学模型，以将发现推广到各种问题，特别是在工程学中。该项目的成果将被用作应用软件开发的垫脚石。将开发一个跨学科的教学计划，以培养能够利用这两个领域的见解的新一代生物学家和工程师。短片纪录片和其他教学工具将吸引公众。该项目旨在提供详细的经验数据，说明社会昆虫群体如何产生有效和强大的劳动分工，以及一个更广泛的理论框架，将提供对优化的、自组织的任务分配的见解，该任务分配在复杂系统中广泛应用。单独标记的蚂蚁和半自动跟踪系统将促进全面的数据收集。例如，工作需求的波动是否会导致活动水平的变化？这将表明在蚁群中发现的许多明显不活跃的蚂蚁是否是必要的储备，以及任务分配策略的灵活性。任务分配对昆虫群体适应度的影响将被直接测量。发展模型将用于预测特定战略可能如何导致不活跃，以及替代战略在准确性、灵活性、稳健性和专业化方面的表现如何。在分布式计算理论中，这项工作将通过提供更强大的模型来推动极限，这些模型考虑了离散、连续、动态和概率行为的组合。研究人员还将举办生物分布式算法年度研讨会，汇聚生物学、计算和机器人领域的顶尖研究人员。

One of the most important, perhaps the biggest unanswered question in biology is how a collection of relatively simple parts can form structures that are organized, effective and often beautiful. This occurs in the origin of life, where clusters of molecules form cells; in development, where initially unspecialized cells form an embryo; and in many other systems, including insect colonies, where an aggregation of small insects generates adaptive group behavior. The same phenomenon also affects humans more directly, where computer clusters, power grids, and people in organizations display unforeseen group-level behavior. This project specifically investigates the behavioral rules that individual units in such groups may use to divide up tasks. Division of labor plays an important role in many collective systems and a systematic understanding of how best to achieve it is lacking. This project will make substantive contributions to the fields of Animal Behavior, Computer Science and Engineering. Ants will be used as an empirical study system and mathematical models will be developed to generalize findings to a variety of questions, particularly in engineering. Results from this project will be used as a stepping-stone to applied software development. An interdisciplinary teaching program will be developed to train a new generation of biologists and engineers who can make use of insights from both of these fields. Short film documentaries and other teaching tools will engage the general public.This project aims to provide both detailed empirical data on how social insect colonies generate an efficient and robust division of labor and a broader theoretical framework that will deliver insights on optimized, self-organized task allocation that applies widely across complex systems. Individually marked ants and a semi-automated tracking system will facilitate comprehensive data collection. For example, do fluctuations in the need for work drive changing activity levels? This will show whether the many apparently inactive ants found in colonies are necessary reserves and how flexible task allocation strategies are. The effect of task allocation on insect colony fitness will be directly measured. The development models will be used to predict how inactivity may result from particular strategies and how alternative strategies perform in terms of accuracy, flexibility, robustness and specialization. In distributed computing theory, this work will push the envelope by providing more powerful models that take into account a combination of discrete, continuous, dynamic and probabilistic behavior. The investigators will also hold an annual workshop on Biological Distributed Algorithms, bringing together top researchers in biology, computing and robotics.