A Multi-agent Organizational Model for a Snow Storm Crisis Management

The organizational aspects are currently getting a great attention within the multi-agent systems (MAS) community. The motivation towards this trend is finding a way to handle the increasing complexity and distribution of modern agent-based applications using higher order abstractions such as agent organizations. It is a transition from concerning the micro level (individual agents) to concerning the macro level (the whole system) to handle complexity. A large number of MAS organizational models can be found in MAS literature. Some of them adopt the ACMAS (Agent-Centered MAS) viewpoint and others adopt the OCMAS (Organizational-Centered MAS) viewpoint. Each of the ACMAS and OCMAS viewpoints has its advantages and disadvantages; therefore, combining them into a hybrid model is expected to give us the chance to take benefit of their advantages and avoid their disadvantages. This chapter presents our recent work towards the conceptual design of a hybrid MAS organizational model that combines both of the ACMAS and OCMAS viewpoints.

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A multi-agent system for learner assessment in serious games: Application to learning processes in crisis management

IEEE 7th International Conference on Research Challenges in Information Science (RCIS) ◽

10.1109/rcis.2013.6577689 ◽

2013 ◽

Cited By ~ 2

Author(s):

M'hammed Ali Oulhaci ◽

Erwan Tranvouez ◽

Sebastien Fournier ◽

Bernard Espinasse

Keyword(s):

Crisis Management ◽

Serious Games ◽

Learning Processes ◽

Multi Agent System ◽

Agent System ◽

Learner Assessment ◽

Multi Agent

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Multi-Agent System Based Wireless Sensor Network for Crisis Management

2010 IEEE Global Telecommunications Conference GLOBECOM 2010 ◽

10.1109/glocom.2010.5683166 ◽

2010 ◽

Cited By ~ 7

Author(s):

Ahmad Sardouk ◽

Majdi Mansouri ◽

Leila Merghem-Boulahia ◽

Dominique Gaiti ◽

Rana Rahim-Amoud

Keyword(s):

Wireless Sensor Network ◽

Crisis Management ◽

Sensor Network ◽

Wireless Sensor ◽

Multi Agent System ◽

Agent System ◽

Multi Agent

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Flood Management in Aqala through an Agent-Based Solution and Crowdsourcing Services in an Enterprise Geospatial Information System

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi8090420 ◽

2019 ◽

Vol 8 (9) ◽

pp. 420 ◽

Cited By ~ 1

Author(s):

Hooshang Eivazy ◽

Mohammad Reza Malek

Keyword(s):

Information System ◽

Crisis Management ◽

Flood Management ◽

Mathematical Framework ◽

Geospatial Information ◽

Agent Based ◽

Data Schema ◽

Management Processes ◽

Present Solution ◽

Multi Agent

Propagating crowdsourcing services via a wireless network can be an appropriate solution to using the potential of crowds in crisis management processes. The present study aimed to deploy crowdsourcing services properly to spatial urgent requests. Composing such atomic services can conquer sophisticated crisis management. In addition, the conducted propagated services guide people through crisis fields and allow managers to use crowd potential appropriately. The use of such services requires a suitable automated allocation method, along with a proper approach to arranging the sequence of propagating services. The solution uses a mathematical framework in the context of a GIS (Geospatial Information System) in order to construct an allocation approach. Solution elements are set out in a multi-agent environment structure, which simulate disaster field objects. Agents which are dynamically linked to objects in a crisis field, interact with each other in a competitive environment, and the results in forming crowdsourcing services are used to guide crowds in the crisis field via the crowdsourcing services. The present solution was implemented through a proper data schema in a powerful geodatabase, along with various users with specialized interfaces. Finally, a solution and crowdsourcing service was tested in the context of a GIS in the 2019 Aqala flood disaster in Iran and other complement scenarios. The allocating performance and operation of other system elements were acceptable and reduced indicators, such as rescuer fatigue and delay time. Crowdsourcing service was positioned well in the solution and provided good performance among the elements of the Geospatial Information System.

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