|Home||<< 1 >>|
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 Ė 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 planís local and global flexibility.
Keywords: crisis management; flexibility; multi-agent system; decision making under uncertainty; negotiation
Tina Comes, Claudine Conrado, Michael Hiete, Michiel Kamermans, Gregor Pavlin, & Niek Wijngaards. (2010). An intelligent decision support system for decision making under uncertainty in distributed reasoning frameworks. 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: This paper presents an intelligent system facilitating better-informed decision making under severe uncertainty as found in emergency management. The construction of decision-relevant scenarios, being coherent and plausible descriptions of a situation and its future development, is used as a rationale for collecting, organizing, filtering and processing information for decision making. The development of scenarios is geared to assessing decision alternatives, thus avoiding time-consuming analysis and processing of irrelevant information. The scenarios are constructed in a distributed setting allowing for a flexible adaptation of reasoning (principles and processes) to the problem at hand and the information available. This approach ensures that each decision can be founded on a coherent set of scenarios, which was constructed using the best expertise available within a limited timeframe. Our theoretical framework is demonstrated in a distributed decision support system by orchestrating both automated systems and human experts into workflows tailored to each specific problem.
Keywords: Automation; Civil defense; Decision making; Decision support systems; Disasters; Expert systems; Information systems; Intelligent systems; Multi agent systems; Risk management; Decision making under uncertainty; Distributed decision support systems; Distributed reasonings; Emergency management; Intelligent decision support systems; Multi-criteria decision analysis; Scenario-based; Theoretical framework; Information filtering
Track: Intelligent Systems