An Investigation of Regulatory Decision Making by Automated Decision Makers

Lead Research Organisation: University of Nottingham
Department Name: School of Computer Science


In this proposal we will investigate if we can simulate regulatory group decision making utilising an environment of cooperating and automated decision makers. This ambitious project comprises a multi-disciplinary, inter-institutional team drawn from Computer Science, Psychology and Industrial and Manufacturing Science. The four investigators will be supported by a three year PhD student, based at Cranfield, and a two year Nottingham based research assistant.The first phase of the project will define the regulatory decision contexts (environmental planning, permitting, policy development), individual roles and personality influences. These factors will be incorporated in the simulation environment in the second phase of the project and the resulting system will be analysed in the final phase.The second phase of the project will take the outputs from phase one and create a simulation environment. This environment will initially be built using agent based technology, but other machine learning approaches will be investigated as appropriate.The final phase will involve all members of the team in analysing the resulting system and calibrating its parameters in order to emulate group decision making processes as closely as possible.A key feature of this proposal are 2-day workshops at nine monthly intervals in order for the whole team (investigators, PhD student, RA and project partners) to work together in a focused way.
Description Complex regulatory decisions about risk rely on the brokering of evidence between providers and recipients, and involve personality and power relationships that influence the confidence that recipients may place in the sufficiency of evidence and, therefore, the decision outcome. We explore these relationships in an agent-based model; drawing on concepts from environmental risk science, decision psychology and computer simulation.
Exploitation Route The research we have conducted is applicable to anybody who is faced with complex regulatory decisions, where an element of risk is involved. Therefore, it might be of interest to government agencies, regulatory bodies, large/complex organisations, as well agencies that have to decide on policy given a range of stakeholders.
Sectors Communities and Social Services/Policy




Description This project produced five high quality journal papers, with the latest paper being published in 2014, demonstrating that the research team was still working together long after the research program has been completed (from a funding point of view). We are pleased to see that the papers we produced are starting to attract citations, indicating that other reseachers are finding our work is useful. In particular, the 2009 paper has received 11 citations (as at 12 Nov 2014) which are speard a variety of disciplines, including medicine, the environment and logistics. We believe this shows that the research is applicable to many different disciplines.
First Year Of Impact 2009
Sector Environment,Transport
Impact Types Economic

Policy & public services

Description Dept for Env Food & Rural Affairs DEFRA 
Organisation Department For Environment, Food And Rural Affairs (DEFRA)
Country United Kingdom 
Sector Public 
Start Year 2006
Description University of Oxford 
Organisation University of Oxford
Country United Kingdom 
Sector Academic/University 
Start Year 2006