Hans Abbink, Roel Van Dijk, Tamas Dobos, Mark Hoogendoorn, Catholijn M. Jonker, Savas Konur, et al. (2004). Automated support for adaptive incident management. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management (pp. 69–74). Brussels: Royal Flemish Academy of Belgium.
Abstract: The project CIM, started in 2003, addresses the problem of automated support for incident management. In this paper some intermediate results are shown, especially on automated support of analysis of errors in traces of incident management. For such traces it can be checked automatically which dynamic properties hold or fail. The potential of the approach is shown in the formal analysis of a given empirical trace. The approach can also be applied in conjunction with simulation experiments. © Proceedings ISCRAM 2004.
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Aïdin Sumic, Emna Amdouni, Thierry Vidal, & Hedi Karray. (2022). Towards Flexibility Sharing in Multi-agent Dynamic Planning: The Case of the Health Crisis. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 274–284). Tarbes, France.
Abstract: Planning problems in a crisis context are a highly uncertain environment where health facilities must cooperate in providing health services to their patients. We focus on the health crisis in France due to the COVID19 pandemic. In fact, the lack of appropriate scheduling tools, resources, and communication leads hospitals to be submerged by infected patients and forced to transfer them to other hospitals. In this work we aim to provide a global solution to such planning problems to improve the current French health system. We introduce a cooperative approach called OPPIC (Operational Planning Platform for Inter-healthcare Coordination). OPPIC is based on a decentralized system, where health facilities plan is dynamic, flexible, robust to uncertainty, and respond to goals and optimization criteria. This paper proposed a first planning model to OPPIC and provided a first way of negotiation between health facilities based on their plan’s local and global flexibility.
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Guruprasad Airy, Tracy Mullen, & John Yen. (2009). Market based adaptive resource allocation for distributed rescue teams. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The dynamic nature of real-world rescue scenarios (e.g., military, emergency first response, hurricane relief) requires constant reevaluation of resource assignments. New events can trigger additional resource requirements generating conflicts about how to reassign resources across tasks in an emerging crisis. Reallocation is further complicated as some resources are synergistic (i.e., helicopter and pilot) and many distributed rescue teams have limited information about other teams' status. We show how integrating a team-based multi-agent planning system with standard combinatorial auction methods to dynamically re-allocate resources can maximize overall rescue utility while providing for graceful managed degradation under conditions of extreme stress. The key innovation of our approach is that we explicitly provide a framework that incorporates the costs involved in dynamically switching resources from one task to another. We compare our system's performance against two other approaches.
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Guido Bruinsma, & Robert De Hoog. (2006). Exploring protocols for multidisciplinary disaster response using adaptive workflow simulation. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 53–65). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: The unique and dynamic changing nature in which a disaster unfolds forces emergency personnel involved with the mitigation process to be greatly flexible in their implementation of protocols. In past disasters the incapability of the disaster organization to swiftly adjust the workflow to the changing circumstances, has resulted in unnecessary delays and errors in mitigation. Addressing this issue, we propose and demonstrate a method for simulating disasters for work and protocol optimization in disasters response (TAID), based on the BRAHMS multi-agent modeling and simulation language. Our hypothesis is that this low fidelity simulation environment can effectively simulate work practice in dynamic environments to rearrange workflow and protocols. The results from an initial test simulation of the Hercules disaster at Eindhoven airport in the Netherlands look promising for future and broader application of our disaster simulation method.
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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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Florian Brauner, Julia Maertens, Holger Bracker, Ompe Aimé Mudimu, & Alex Lechleuthner. (2015). Determination of the effectiveness of security measures for low probability but high consequence events: A comparison of multi-agent-simulation & process modelling by experts (L. Palen, M. Buscher, T. Comes, & A. Hughes, Eds.). Kristiansand, Norway: University of Agder (UiA).
Abstract: Due to the increasing danger of terrorist attacks, it is necessary to determine the preventive effects of security measures installed in e.g. public transportation systems. Since, there is no common practice to determine the preventive effects; we developed two different methodologies to analyse those effects, both are suitable for the assessment of security measures. The first method is a semi-quantitative method based on expert-estimations combined with a modelled process of an attack.The second method models the scenarios using a multi-agent-based simulation framework. Simulating a large number of runs, it is possible to derive values for indicators of interest on statistical basis. We show the suitability of both methods by applying them on a practical example of a public transportation system. In this paper we introduce both methodologies, show an exemplary application and present the strengths and weaknesses and how they can be linked to get an increased benefit.
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Faisal Luqman, & Martin Griss. (2011). Leveraging mobile context for effective collaboration and task management. 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: Collaboration and task management is challenging in distributed, dynamically-formed teams, typical in large scale disaster response scenarios. Ineffective collaboration may potentially result in poor performance and loss of life. The increased adoption of sensor rich mobile devices allow for mobile context to be leveraged. In this paper, we present Overseer, an agent-based system that exploits context information from mobile devices to facilitate collaboration and task allocation. We describe how mobile context can be used to create dynamic role-based assignments to enhance collaboration and effective task management.
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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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Maël Arnaud, Carole Adam, & Julie Dugdale. (2017). The role of cognitive biases in reactions to bushfires. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 85–96). Albi, France: Iscram.
Abstract: Human behaviour is influenced by many psychological factors such as emotions, whose role is already widely recognised. Another important factor, and all the more so during disasters where time pressure and stress constrain reasoning, are cognitive biases. In this paper, we present a short overview of the literature on cognitive biases and show how some of these biases are relevant in a particular disaster, the 2009 bushfires in the South-East of Australia. We provide a preliminary formalisation of these cognitive biases in BDI (beliefs, desires, intentions) agents, with the goal of integrating such agents into agent-based models to get more realistic behaviour. We argue that taking such “irrational” behaviours into account in simulation is crucial in order to produce valid results that can be used by emergency managers to better understand the behaviour of the population in future bushfires.
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Miriam Klein, Eric Rigaud, Marcus Wiens, Anouck Adrot, Frank Fiedrich, Nour Kanaan, et al. (2018). A Multi-Agent System for Studying Cross-Border Disaster Resilience. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 135–144). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Resilience to disasters depends on measures taken before, during and after the occurrence of adverse events. These measures require interactions between people belonging to different organizations (public, private, non-profit) and citizens in normal and stressful situations. The efficiency of resilience measures results from the collective interaction of individuals, groups of individuals, and organizations, as well as the situational characteristics of the decision environment. The aim of the French-German research project INCA is to develop a decision support framework for improving cross-border area resilience to disasters. This project comprises the design and the implementation of a multi-agent system with the objective to study the behavioral and organizational implications of cross-border cooperation for crisis management and disaster resilience. The analyzed measures focus on citizens who require medical support and the integration of volunteers into the crisis management procedure. This paper outlines the potentials of the multi-agent system and provides first implementation insights.
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Heiko Roßnagel, & Olaf Junker. (2010). Evaluation of a mobile emergency management system – A simulation approach. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Large public events such as sporting events, concerts, fairs and street festivals are quite common in metropolitan areas. Because of the high frequency of such events and the increasing number of involved parties, those being responsible for the organization and execution have to cope with increasing complexity and shortening time frames for planning and preperation. Because of the high concentration of passengers, unplanned incidents that occur during these public events can have devastating effects and can lead to crises and disasters. Emergency management systems that utilize mobile communication infrastructures can provide prompt information delivery to save human lives. In this paper we propose a system design for mobile emergency management and outline our approach of evaluating this system design using multi-agent based simulation. To make our simulation of passenger movements as realistic as possible we gathered empirical data for a large event as well as for normal rush hour traffic.
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Takuya Oki, & Toshihiro Osaragi. (2016). Wide-area Evacuation Difficulty in Densely-built Wooden Residential Areas. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: In aiming to decrease the number of casualties and people with difficulty in wide-area evacuations due to a large earthquake, it is highly important to visualize and quantify the potential danger in residential areas. In this paper, we construct a multi-agent simulation model, which describes property damage (such as building-collapse, the spread of fire and blocking of streets) and people?s evacuation behavior after an earthquake occurring. Using this simulation model, we quantify the wide-area evacuation difficulty in densely-built wooden residential areas, and evaluate the past project to improve buildings and streets based on this indicator. Furthermore, we demonstrate the effects of adding new evacuation routes between two intersections of streets with narrow width and long distance. Through these case studies, the effectiveness of our simulation model on urban disaster mitigation planning is shown.
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