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

分工，即有机体专门扮演角色并合作生存，是细菌、黏菌、社会性昆虫甚至人类所采用的一种策略。此外，进化中的重大转变，即以前截然不同的个体结合在一起，形成一个更高水平的单位，作为一个单一的生殖实体，也表现出分工。例如，单个细胞结合在一起并专门化成为多细胞有机体。生物学中的一个基本问题是，劳动分工为什么会演变？虽然生物学家对这个问题很感兴趣，但由于历史数据的不完善和漫长的世代时间，用自然系统研究仍然具有挑战性，如果不是不可能的话。这项研究涉及开发一个软件基础设施来研究分工的演变。分工产生的效率收益是为什么群体内的分工演变以及为什么进化中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推动这些进化变化，研究人员研究了数字有机体的种群，这些数字生物体是以开放方式进化的全功能计算机程序。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，以及有助于探索潜在机制的自动数据收集。以Avida数字进化平台为基础，研究人员正在建立一个基础设施，以研究围绕分工进化的主题，包括：(1)学习在基于任务的分工进化中的作用，(2)繁殖成本的增加是否会影响兄弟般的重大转变发生，以及(3)专业化能力是否会激励遗传上截然不同的有机体作为一个群体进行繁殖。

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.