The First Phase of Real-World Discovery: Determining Repeatability and Error of Experiments

Abstract

Using un-repeatable data and forgetting about measurement error are two cardinal sins in empirical sciences. A machine discovery system must be able to handle both before attempting serious discoveries. We describe an application of the discovery system FAHRENHEIT in a science laboratory, focused on the preparatory stage of the empirical discovery process, i.e. the investigation of repeatability and the measurement of error. To cope with real-world empirical discovery, FAHRENHEIT has been reorganized as a distributed multi-process system and a robotic component including external manipulators and measuring instruments. We present the application of FAHRENHEIT to an experiment in which the system discovers repeatability conditions and error in the context of dispensing liquids in a chemistry laboratory. We then present the theory of the process. Many quantitative discovery systems distinguish between dependent and independent control variables. We argue that to handle repeatability and error, independent variables should be divided further into two categories: theory formation variables and experiment refinement variables. The former have been used by BACON, FAHRENHEIT and other empirical discovery systems to re-discover scientific laws. The latter are used to determine the repeatability and error, prior to the system discovery of the main theory using theory formation variables.