Towards Robot Scientists for autonomous scientific discovery
We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical experiments using robotic systems, analyses and interprets the resulting data, and repeats the cycle. We describe our two prototype Robot Scientists: Adam and Eve. Adam has recently proven the potential of such systems by identifying twelve genes responsible for catalysing specific reactions in the metabolic pathways of the yeast Saccharomyces cerevisiae. This work has been formally recorded in great detail using logic. We argue that the reporting of science needs to become fully formalised and that Robot Scientists can help achieve this. This will make scientific information more reproducible and reusable, and promote the integration of computers in scientific reasoning. We believe the greater automation of both the physical and intellectual aspects of scientific investigations to be essential to the future of science. Greater automation improves the accuracy and reliability of experiments, increases the pace of discovery and, in common with conventional laboratory automation, removes tedious and repetitive tasks from the human scientist.
- Towards Robot Scientists for autonomous scientific discovery
- Open Access
- Available under Open Access This content is freely available online to anyone, anywhere at any time.
- Online Date
- January 2010
- Online ISSN
- BioMed Central
- Additional Links
- Author Affiliations
- 1. Computational Biology Group, Department of Computer Science, Penglais Campus, Aberystwyth University, Aberystwyth, SY23 3DB, UK
- 3. School of Engineering and Information, Middlesex University, NW4 4BT, UK
- 2. Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, SY23 3DD, UK