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

BCSP: The Emergence of Inactivity: Adaptive Task Allocation in Complex Distributed Systems, or Why Are There so Many Lazy Ants?
BCSP:不活动的出现:复杂分布式系统中的自适应任务分配,或者为什么有这么多懒蚂蚁?
批准号:
1455983
负责人:
Anna Dornhaus
金额:
$69.5万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-06-01 至 2020-05-31

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中文摘要
翻译
生物学中最重要的问题之一,也许是最大的未解之谜是,相对简单的部分如何形成有组织的,有效的,通常是美丽的结构。这发生在生命的起源中,在那里分子簇形成细胞;在发育中,最初未特化的细胞形成胚胎;在许多其他系统中,包括昆虫群体,小昆虫的聚集产生适应性群体行为。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行为。这个项目专门研究这些小组中的各个单位可能用来分配任务的行为规则。劳动分工在许多集体系统中发挥着重要作用,但人们对如何最好地实现这一点缺乏系统的理解。该项目将对动物行为学、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,以将研究结果推广到各种问题,特别是在工程领域。这个项目的结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,以培养新一代的生物学家和工程师谁可以利用这两个领域的见解。该项目旨在提供关于群居昆虫群体如何产生高效和稳健的劳动分工的详细经验数据,以及更广泛的理论框架,以提供广泛适用于复杂系统的优化自组织任务分配的见解。个别标记的蚂蚁和半自动跟踪系统将有助于全面的数据收集。例如,工作需求的波动是否会推动活动水平的变化?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。将直接测量任务分配对昆虫群体适合度的影响。发展模型将用于预测特定策略如何导致不活动,以及替代策略在准确性、灵活性、稳健性和专业化方面的表现。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信封,这些模型考虑了离散,连续,动态和概率行为的组合。研究人员还将举办一个关于生物分布式算法的年度研讨会,汇集生物学、计算机和机器人领域的顶尖研究人员。
英文摘要
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.
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Collaborative Research: ABI Development: A User-friendly Tool for Highly Accurate Video Tracking
  • 批准号:
    1564521
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.68万
  • 财政年份:
    2016
  • 负责人:
    Anna Dornhaus
  • 依托单位:
Collaborative Proposal: ABI Innovation: Rapid, Interactive, Visual Mining of Biological Motion
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    1262292
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $27.93万
  • 财政年份:
    2013
  • 负责人:
    Anna Dornhaus
  • 依托单位:
Collaborative Proposal: EAGER: Towards Real-time, High throughput Insect Behavior Analysis
  • 批准号:
    1045269
  • 项目类别:
    Standard Grant
  • 资助金额:
    $7.6万
  • 财政年份:
    2010
  • 负责人:
    Anna Dornhaus
  • 依托单位:
Adaptive distribution of morphological specialists in social insects: New insights into the evolution of division of labor
  • 批准号:
    0841756
  • 项目类别:
    Standard Grant
  • 资助金额:
    $45.0万
  • 财政年份:
    2009
  • 负责人:
    Anna Dornhaus
  • 依托单位:
国内基金
海外基金
Exposing Verifiable Consequences of the Emergence of Mass
  • 批准号:
    12135007
  • 项目类别:
    重点项目
  • 资助金额:
    313万元
  • 批准年份:
    2021
  • 负责人:
    Craig Darrian Roberts
  • 依托单位:
拓扑动力系统中熵和emergence理论的研究
  • 批准号:
    12101340
  • 项目类别:
    青年科学基金项目(C类)
  • 资助金额:
    30.0万元
  • 批准年份:
    2021
  • 负责人:
    季泳
  • 依托单位: