Autonomous Experimentation in Practice
Citation
Yager, K.G. "Autonomous Experimentation in Practice"
Methods and Applications of Autonomous Experimentation, Taylor & Francis 2023,
Chapter 1 ISBN 978–1032314655.
doi: 10.1201/9781003359593Summary
We introduce the concept of autonomous experimentation.
Abstract
Autonomous Experimentation (AE) is an emerging paradigm for accelerating scientific discovery, leveraging artificial intelligence and machine-learning methods to automate the entire experimental loop, including the decision-making step. AE combines advancements in hardware automation, data analytics, modeling, and active learning to augment a scientific instrument, enabling it to autonomously explore the search space corresponding to a problem of interest. AE can be deployed quite easily in any context where automation is feasible, by connecting a decision-making algorithm in between data analysis and machine-command modules. AE holds the promise of radically accelerating discovery, by liberating the human researcher to operate at a higher level, and focus on scientific understanding rather than experimental management.
