About the Project
This project is one of a number funded by the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding.
The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students.
Please note that of the total number of projects within the competition, up to 15 studentships will be filled.
Location
Streatham Campus, Exeter
Project Description
Evolutionary algorithms (EAs) are nature-inspired techniques that are widely used to optimise complex problems in science and industry. Interactive EAs incorporate an expert from the problem domain to incorporate their knowledge into the optimisation process, which can greatly improve results; a problem, however, is that EAs are highly complex systems and do not work in terms with which a typical user is familiar, making them difficult to relate to. As such, developing intuitive systems for human-algorithm interaction is vital. This work will use the principles of human-computer interaction (HCI) to develop new mechanisms of interaction between the user and algorithm, including the capturing of domain expertise and visualisation of solution sets. It will also seek to enable interaction with the whole evolutionary processes, particularly the mechanisms used to generate new solutions. Examples of areas that will be investigated include:
Interaction with the application of crossover and mutation operators, and the effect their use has on the population.
Visualisation within dynamic and uncertain environments – illustrating, for example, how the fitness landscape changes over time.
The relationship between solutions and their corresponding objective(s).
Application to other nature-inspired techniques, and related algorithms such as drive hyper-heuristics.
Evaluation of the human-algorithm interaction methods will be conducted rigorously using HCI research methods drawn from an interdisciplinary supervision team from Computer Science and Psychology. Since an objective of the project is to make EAs more intuitive, a natural consequence will be an increased inclination among practitioners to use them. Survey methods, such as questionnaires and interviews/focus groups of users will be used to evaluate the quality of interaction and visualisation mechanisms. User studies and observational methods will be employed to understand users’ experiences of the systems to enable further refinement and implementation. Furthermore, crowd sourcing and citizen science can be used to ensure a large number of respondents, in order to make the assessment as scientifically robust as possible.
The role of the student will be to design and implement interaction mechanisms and visualisations of data arising from evolutionary computation. This will require generating experimental data that can be visualised from a range of optimisation problem types, using a variety of types of EA. Having developed these methods, they will be responsible for evaluating the use of their methods, and writing them up for presentation at leading international conferences and top journals in HCI and evolutionary algorithms.
Entry Requirements
You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in Computer Science. Experience in human-computer interaction and/or nature-inspired computation is desirable.
If English is not your first language you will need to meet the English language requirements and provide proof of proficiency.
The majority of the studentships are available for applicants who are ordinarily resident in the UK and are classed as UK/EU for tuition fee purposes. If you have not resided in the UK for at least 3 years prior to the start of the studentship, you are not eligible for a maintenance allowance so you would need an alternative source of funding for living costs. To be eligible for fees-only funding you must be ordinarily resident in a member state of the EU.
Applicants who are classed as International for tuition fee purposes are NOT eligible for funding. International students interested in studying at the University of Exeter should search our funding database for alternative options.
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