A Digital Evolution Infrastructure for Experimental Investigations into the Evolution of Division of Labor

用于劳动分工演化实验研究的数字演化基础设施

• 批准号: 1122620
• 负责人: Heather Goldsby
• 金额: $ 24万
• 依托单位: Goldsby Heather J
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1122620&HistoricalAwards=false
• 关键词: Digital; Evolution; Infrastructure; Experimental; Investigations

Division of labor, where organisms specialize on roles and cooperate to survive, is a strategy employed by bacteria, slime molds, eusocial insects, and even humans. Moreover, major transitions in evolution, where formerly distinct individuals join together in a higher-level unit that functions as a single reproductive entity, also exhibit division of labor. For example, single cells join together and specialize to become a multicellular organism. A fundamental question in biology is why does division of labor evolve? While biologists are fascinated by this question, it remains challenging, if not impossible, to study with natural systems due to imperfections in the historical data and long generation times. This research involves developing a software infrastructure to investigate the evolution of division of labor.Efficiency gains resulting from division of labor are a central component of hypotheses for why division of labor evolves within groups and why major transitions in evolution occur. To understand whether efficiency gains are sufficient to motivate these evolutionary changes, the investigators study populations of digital organisms, which are fully-functional computer programs that evolve in an open-ended manner. In contrast to experimental evolution with natural systems, digital organisms have rapid generation times, unparalleled experimental control, and automated data collection that facilitates explorations of underlying mechanisms. Using the Avida digital evolution platform as a foundation, the researchers are building an infrastructure to investigate topics surrounding the evolution of division of labor, including: (1) the role of learning in the evolution of task-based division of labor, (2) whether an increased cost of reproduction influences when fraternal major transitions occur, and (3) whether specialization capabilities motivate genetically distinct organisms to reproduce as a group.

劳动分工是指生物体分工并合作生存，这是细菌、黏菌、真社会性昆虫甚至人类都采用的一种策略。此外，在进化的重大转变中，以前不同的个体在一个更高级别的单位中结合在一起，作为一个单一的生殖实体，也表现出劳动分工。例如，单细胞结合在一起并特化成为多细胞生物。生物学的一个基本问题是为什么劳动分工会进化？虽然生物学家对这个问题很着迷，但由于历史数据的不完善和长时间的生成，用自然系统进行研究仍然具有挑战性，如果不是不可能的话。本研究包括开发一个软件基础设施来研究劳动分工的演变。劳动分工带来的效率提高是解释为什么分工在群体内进化以及为什么进化过程中会发生重大转变的假设的核心组成部分。为了了解效率的提高是否足以激发这些进化变化，研究人员研究了数字生物的种群，它们是功能齐全的计算机程序，以开放式的方式进化。与自然系统的实验进化相比，数字生物具有快速的生成时间，无与伦比的实验控制和自动化数据收集，有助于探索潜在机制。利用Avida数字进化平台作为基础，研究人员正在构建一个基础设施，以调查围绕劳动分工进化的主题，包括：(1)学习在基于任务的劳动分工进化中的作用，(2)当兄弟重大转变发生时，繁殖成本的增加是否会影响，以及(3)专业化能力是否会激励遗传上不同的生物体作为一个群体进行繁殖。