Distributed Hypothesis Generation and Evaluation (EPSRC CDT In Distributed Algorithms)

Are you looking for a challenging and exciting PhD in data science focused on using argumentation theory to develop collaborative tools while providing opportunities to test solutions on real mysteries? A fully funded PhD awaits your input.

This PhD will look to develop approaches to support analysts and semi-automated agents in collaboratively performing hypothesis generation and evaluation in an intelligence scenario. The approaches should look utilise argumentation theory, a mathematical construction representing conflicts between arguments. Argumentation can be represented computationally as an ontology which allows a linked data approach to distributed analysis.

Approaches should be developed to allow analysts with particular expertise to contribute their knowledge to different parts of an intelligence analysis in a collaborative manner by generating sub-arguments which are coherent with the analysis as a whole. Analysts or agents, using a well-defined theory of abstract argumentation, may then evaluate the hypotheses, which may suggest further collection of information or require refinement of hypotheses. Intelligence analysis should be considered as a cycle and therefore all stages of the process should be compatible with collaborative and distributed analysis. The approaches developed should be validated against other intelligence analysis techniques. Care will be needed to mitigate the potential for biases in the system.

The intelligence cycle consists of understanding the information available, generating hypotheses, based on the analysts’ situational understanding and the intelligence available and evaluating these hypotheses using the available evidence and structural analytical techniques, eg Analysis of Competing Hypotheses. In each of these steps, analysts, and in future semi-autonomous agents, perform reasoning based on different intelligence available and their background knowledge. Allowing analysts to collaborate effectively on intelligence problems could improve the quality of analyses and reduce biases in an analysis.

This project is part of the EPSRC Centre for Doctoral Training in Distributed Algorithms: The What, How and where of Next-Generation Data Science www.liverpool.ac.uk/distributed-algorithms-cdt

This studentship has been developed in partnership with the UK’s Defence Science and Technology Laboratory (Dstl). Dstl ensures that innovative science and technology contribute to the defence and security of the UK. Dstl will help define the problem and provide direction for the research. Subject to nationality and security considerations, there will be the opportunity to work closely with Dstl, including opportunities to work at their sites.

This project starts 1 October 2020 (Covid-19 Working Practices available).

This project will aim to extend previous work on computational models of argumentation to be applicable in a distributed and collaborative setting. The research will build on other work being done at, for example, the University of Liverpool, the University of Dundee, North Carolina University and Melbourne University. International collaboration (and visits, assuming Covid-19 working practices allow) is anticipated.

Current work at the University of Liverpool is developing an environment that enables tools that can support intelligence analysis to be quantitatively assessed in the context of a genuine mystery (related to a train crash) and developing tools that enable hypotheses to be assessed and iteratively refined. Current work at the University of Dundee is investigating automated extraction of hypotheses from argumentation maps. This PhD will build on the solid foundation offered by these ongoing bodies of research but will focus on the distributed and collaborative aspects of the problem.

For information technical queries please contact Profs Katie Atkinson [Email Address Removed] and/or Simon Maskell [Email Address Removed]

For general application process queries contact [Email Address Removed]

To apply for this Studentship please follow the DA CDT Application Instructions: https://www.liverpool.ac.uk/research/research-themes/digital/cdt-distributed-algorithms/opportunities/. Submit an application for an Electrical Engineering PhD via the University of Liverpool’s online PhD application platform (https://www.liverpool.ac.uk/study/postgraduate-research/how-to-apply/) and provide the studentship title and supervisor details when prompted. Should you wish to apply for more than one project, please provide a ranked list of those you are interested in.

For a full list of the entry criteria and a recruitment timeline (including interview dates etc), Please see our website www.liverpool.ac.uk/distributed-algorithms-cdt