Experiencing Self-adaptive MAS for Real-Time Decision Support Systems

Georgé, Jean‐Pierre; Peyruqueou, Sylvain; Régis, Christine; Glize, Pierre

doi:10.1007/978-3-642-00487-2_32

Cited by 9 publications

(8 citation statements)

References 4 publications

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“…Georgé et al [37] and Scerri et al [38] developed self-adaptive ABM systems of devices and robotics (boats), which supported realtime flood forecasting and offered quick situation awareness and relief supplies. ABM combined with a virtual geographic environment (VGE) has demonstrated the capacity to identify businesses affected by flooding in the UK [39], though the introduced model did not involve response activities of the businesses and thus did not make full use of the advantages of ABM.…”

Section: Agent-based Modeling In Flood Studiesmentioning

confidence: 99%

Assessment of Flood Losses with Household Responses: Agent-Based Simulation in an Urban Catchment Area

Yang

Scheffran²,

Süsser

et al. 2018

Environ Model Assess

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Densely populated coastal urban areas are often exposed to multiple hazards, in particular floods and storms. Flood defenses and other engineering measures contribute to the mitigation of flood hazards, but a holistic approach to flood risk management should consider other interventions from the human side, including warning information, adaptive behavior, people/property evacuation, and the multilateral relief in local communities. There are few simulation approaches to consider these factors, and these typically focus on collective human actions. This paper presents an agentbased model that simulates flood response preferences and actions taken within individual households to reduce flood losses. The model implements a human response framework in which agents assess different flood scenarios according to warning information and decide whether and how much they invest in response measures to reduce potential inundation damages. A case study has been carried out in the Ng Tung River basin, an urbanized watershed in northern Hong Kong. Adopting a digital elevation model (DEM) as the modeling environment and a building map of household locations in the case area, the model considers the characteristics of households and the flood response behavior of their occupants. We found that property value, warning information, and storm conditions all influence household losses, with downstream and high density areas being particularly vulnerable. Results further indicate (i) that a flood warning system, which provides timely, accurate, and broad coverage rainstorm warning, can reduce flood losses by 30-40%; and (ii) to reduce losses, it is more effective and cheaper to invest early in response measures than late actions. This dynamic agent-based modeling approach is an innovative attempt to quantify and model the role of human responses in flood loss assessments. The model is demonstrated being useful for analyzing household scale flood losses and responses and it has the potential to contribute to flood emergency planning resource allocation in pluvial flood incidents.Keywords Flood risk and damage . Flood loss assessment . Adaptation and response . Urban area . Agent-based modeling . Pearl River Delta .

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Section: Agent-based Modeling In Flood Studiesmentioning

confidence: 99%

Assessment of Flood Losses with Household Responses: Agent-Based Simulation in an Urban Catchment Area

Yang

Scheffran²,

Süsser

et al. 2018

Environ Model Assess

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“…After our taxonomy proposed in [22], experiments that support the use of patterns to build self-adaptive systems are still missing, and that is why we proceed with our work. From our knowledge, there are no works that use agents to simulate self-adaptive systems, exception of the use of AMAS proposed for example by [4] and [13].…”

Section: Related Workmentioning

confidence: 99%

Patterns for self-adaptive systems: agent-based simulations

Puviani¹,

Cabri²,

Zambonelli³

2015

EAI Endorsed Transactions on Self-Adaptive Systems

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Self-adaptive systems are distributed computing systems that can adapt their behavior and structure to different kinds of conditions. This adaptation does not concern the single components only, but the entire system. In a previous work we have identified several patterns for self-adaptation, classifying them by means of a taxonomy, which aims at being a support for developers of self-adaptive systems. Starting from that theoretical work, we have simulated the described self-adaptation patterns, in order to better understand the concrete and real features of each pattern. The contribution of this paper is to report about the simulation work of three patterns as examples, detailing how it was carried out, in order to provide a further support for the developers.

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“…After our taxonomy proposed in (Puviani et al, 2013), experiments that support the use of patterns to build self-adaptive systems are still missing, and that is why we proceed with our work. From our knowledge, there is no work that uses agents to simulate self-adaptive systems, exception of the use of AMAS proposed for example by (Bonabeau et al, 1999) and (Georgé et al, 2009).…”

Section: Related Workmentioning

confidence: 99%

Agent-based Simulations of Patterns for Self-adaptive Systems

Puviani

Cabri

Zambonelli

2014

Proceedings of the 6th International Conference on Agents and Artificial Intelligence

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Self-adaptive systems are distributed computing systems composed of different components that can adapt their behavior to different kinds of conditions. This adaptation does not concern the single components only, but the entire system. In a previous work we have identified several patterns for self-adaptation, classifying them by means of a taxonomy, which aims at being a support for developers of self-adaptive systems. Starting from that theoretical work, we have simulated the described self-adaptation patterns, in order to better understand the concrete and real features of each pattern. The contribution of this paper is to report about the simulation work, detailing how it was carried out, and to present a "table of applicability" that completes the initial taxonomy of patterns and provides a further support for the developers.

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Experiencing Self-adaptive MAS for Real-Time Decision Support Systems

Cited by 9 publications

References 4 publications

Assessment of Flood Losses with Household Responses: Agent-Based Simulation in an Urban Catchment Area

Assessment of Flood Losses with Household Responses: Agent-Based Simulation in an Urban Catchment Area

Patterns for self-adaptive systems: agent-based simulations

Agent-based Simulations of Patterns for Self-adaptive Systems

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