Dobson, S. orcid.org/0000-0001-5800-6729, Burkitt, M., Breslin, D. et al. (1 more author) (2016) Developing an ABM-driven Decision Support System in the Emergency Services. In: Proceedings of the 18th International Conference on Enterprise Information Systems. Proceedings of the 18th International Conference on Enterprise Information Systems, 25-28 Apr 2016, Rome, Italy. SCITEPRESS - Science and Technology Publications, Setúbal, Portugal, pp. 151-157. ISBN: 978-989-758-187-8.
Abstract
The research presented here outlines an application of Agent-Based Modelling (ABM) used to support strategic decision-making in the emergency services. Here the resulting ABM-driven Decision Support System (DSS) (called 'Premonition') is designed to help practitioners engage with a complex and dynamic environment of co-evolving fire risk behaviours through time. Social change is presented here as a process by which behaviours co-evolve within connected networks of agents. ABM is identified as a beneficial approach to simulate changing household behaviours and the influence of social networks, environmental factors, and also fire service interventions within the Sheffield City region, UK. This project seeks to develop a DSS which supports the stages of 'intelligence', 'design', and 'choice' as the decision-maker moves from identifying problem areas, establishing possible strategies for intervention, and predicting possible outcomes of alternative courses of action.
Metadata
| Item Type: | Proceedings Paper |
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| Authors/Creators: |
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| Keywords: | Decision Support System; Co-evolution; Connectivity; Agent-Based Model; Domestic Fire Risk Behaviour |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Arts, Humanities and Cultures (Leeds) > Performance and Cultural Industries (Leeds) |
| Date Deposited: | 18 Nov 2025 15:17 |
| Last Modified: | 18 Nov 2025 15:22 |
| Published Version: | https://dl.acm.org/doi/10.5220/0005773501510157 |
| Status: | Published |
| Publisher: | SCITEPRESS - Science and Technology Publications |
| Identification Number: | 10.5220/0005773501510157 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:234415 |

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