Opportunities for Automated Workflow and Planning with Robot Scientists

A natural extension of the trend of increased involvement in science is the concept of a Robot Scientist [King et al. (2004),King et al. (2009)]. A Robot Scientist automatically: originates hypotheses to explain observations, devises experiments to test these hypotheses, physically runs the experiments using laboratory robotics, interprets the results to change the probability of hypotheses, and then repeats the cycle (Figure 1). Robot Scientists can autonomously execute high-throughput hypothesis led research. In addition to automating experimentation Robot Scientists are well suited to recording scientific knowledge: as the experiments are conceived and executed automatically by computer, it is possible to completely capture and digitally curate all aspects of the scientific process [King et al. (2009)]). The first Robot Scientists are Adam and Eve (Figure 2). The advances that distinguish Adam and Eve from other complex laboratory systems (such as high-throughput drug-screening pipelines, and X-ray crystallography crystal-screening systems) are their AI software, their many complex internal cycles, and their ability to execute individually planned cycles of experiments in highthroughput. Adam was designed to plan and execute microbiological experiments. Adam was fully automated and there is no essential requirement for a technician, except to periodically add laboratory consumables and remove waste. Adam was the first machine demonstrated to have autonomously discovered novel scientific knowledge [King et al. (2009)]. Eve is designed to automate drug discovery. There are many opportunities to improve Adam and Eve using automated workflows and planning. Below I describe some of these opportunities in Adam. The target of