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.