| EPSRC Reference: |
EP/K035959/1 |
| Title: |
Symbolic Support for Scientific Discovery in Systems Biology |
| Principal Investigator: |
Ray, Dr O |
| Other Investigators: |
|
| Researcher Co-Investigators: |
|
| Project Partners: |
|
| Department: |
Computer Science |
| Organisation: |
University of Bristol |
| Scheme: |
First Grant - Revised 2009 |
| Starts: |
31 January 2014 |
Ends: |
30 April 2015 |
Value (£): |
98,673
|
| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Bioinformatics |
| Robotics & Autonomy |
|
|
| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
|
|
| Related Grants: |
|
| Panel History: |
| Panel Date | Panel Name | Outcome |
|
27 Feb 2013
|
EPSRC ICT Responsive Mode - Feb 2013
|
Announced
|
|
|
Summary on Grant Application Form |
The aim of this proposal is to advance the UK's world-leading research on the automation of science by developing novel Artificial Intelligence (AI) support for an existing laboratory robot called Eve (whose predecessor Adam was popularised by Time Magazine and Science in 2009). The purpose of this project is to develop a new logic-based reasoning tool that will allow robots to correct errors in their knowledge. Unlike prior work aimed at extending knowledge that is incomplete, we argue such machines also need the ability to revise knowledge that is incorrect. Indeed, we suggest the capacity to make (and learn from) mistakes is an indispensible part of scientific reasoning. Thus our goals are to realise this ability in a software system for automating intelligent inference about scientific theories and experiments and to demonstrate its benefit in a genuine application of Eve. We believe this will pave the way to a new era in which Robot Scientists will be more productive, more cost-effective, and better able to assist humans in all parts of scientific method.
This project is based on the hypothesis that ground-breaking advances in a field of AI known as Answer Set Programming (ASP) can be used to develop a novel form of (multi-semantic meta-logical) reasoning that will give Robot Scientists the ability to continuously revise and extend their knowledge. Evidence to support this claim is provided by 2 preliminary studies which link the applicant's previous work on the integration of abductive and inductive inference with the robot Adam and a leading ASP system called Clasp. The 1st study showed how a combination of non-monotonic and non-deductive logic can be used to revise a state-of-the-art metabolic model of yeast metabolism in order to fit data seen by Adam; but it also showed a further combination of meta-logical and multi-semantic logic was needed to design new experiments for testing the proposed revisions. The 2nd study suggests how a combination of features recently included in Clasp can be used to do this. Hence this proposal affords a timely opportunity to draw together and build upon these complementary strands of research in a way that will open the door to exciting new opportunities for scientific discovery in systems biology.
The most direct beneficiaries of this work will be our collaborators in the Robot Scientist group (now at the Univ. of Manchester) as our software will enable their robot to correct mistakes in its knowledge and thereby allow the continual evolution of scientific models through many cycles of analysis and experiment. This will represent a major step towards Robot Scientists that participate more effectively in science. By making our tools portable we hope to facilitate their application in other tasks that will benefit from their enhanced reasoning abilities. These tasks include planned follow-on work in the modelling of social insect behaviour (previously studied by our research group) and the automation of some aspects of legal reasoning (recently formalised in argumentation theory). We also plan to study probabilistic extensions of this research that can be built on the logical foundations we will lay. Once our system has been deployed on the Robot Scientist, we also hope to use data generated by planned applications of Eve in high-throughput drug screens to improve our understanding of living organisms.
|
|
Key Findings |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Potential use in non-academic contexts |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Impacts |
|
| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
|
| Date Materialised |
|
|
|
|
Sectors submitted by the Researcher |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
| Project URL: |
|
| Further Information: |
|
| Organisation Website: |
http://www.bris.ac.uk |