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José Miguel Castillo. (2011). An agent-based approach to envision the future. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The need to envision the future is not new; it has existed since the beginning of human-kind. What it is new is the applicable technology that is available in a specific period of time. It is vital to research in the field of methods, techniques and tools that allow us to foresee the future. Although this problem is common to any area, an urgent solution is required to those with critical social repercussions. It is not usual to find a critical social system which evolves according to predictable guidelines or tendencies. This paper presents a solution to model the opinions of an experts group with the aim of predicting possible future scenarios. This paper includes the description of a specific process to elaborate the information elicited from the experts by using fuzzy logic and the development of multi-agent systems (MAS) to automate the creation of such scenarios.
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Cendrella Chahine, Thierry Vidal, Mohamad El Falou, & François Pérès. (2022). Multi-Agent Dynamic Planning Architectures for Crisis Rescue Plans. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 243–255). Tarbes, France.
Abstract: We are interested in rescue management in crises such as in terrorist attacks. Today, there are emergency plans that take into account all the stakeholders involved in a crisis depending on the event type, magnitude and place. Unfortunately, they do not anticipate the evolution of the crisis situation such as traffic and hospital overcrowding. In addition, decisions are taken after the information has been passed from the operational level to higher levels. This work focuses on the operational level of the emergency plan. What will happen if the actors at this level, can make certain decisions without escalating the information to higher levels? To answer this question, a multi-agent dynamic planning approach is proposed and it will be tested in two different architectures in order to see how much autonomy can be given to an agent and how they coordinate to save the victims.
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Lyuba Mancheva, Adam Carole, & Dugdale Julie. (2019). Multi-agent geospatial simulation of human interactions and behaviour in bushfires. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Understanding human behaviour and interactions in risk situations may help to improve crisis management
strategies in order to avoid the worst scenarios. In this paper we present a geospatial agent-based model and
simulation of human behaviour in bushfires. We have modelled the social interactions between different actors
involved in bushfires such as firefighter, police, emergency centre managers and civilians. We use the Belief,
Desire and Intention (BDI) architecture to model realistic human behaviour, and the FIPA-ACL standard to
model the communications. We use geospatial data to represent the environment in a realistic way. We show
how the model has been implemented and how we have unified the communications model and the BDI
architecture. Finally, we compare the processing time of two implementations of our model representing a 2D
simple and a 3D GIS environment.
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