Modeling Malaria with Multi-Agent Systems

Rateb, Fatima; Pavard, Bernard; Bellamine-BenSaoud, Narjès; Merelo, J. J.; Arenas, M. G.

doi:10.4018/9781599049410.ch102

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“…Our own previous works in the design of such organisations, e.g. Air Traffic Control, emergency medical control room, and space control centres, used a multi agent simulation approach in order to empirically study the advantages and disadvantages of complex emergent organisations [24]. From these studies we were able to use these multi-agent models to design complex control rooms [23].…”

Section: Introductionmentioning

confidence: 99%

Coupling agent based simulation with dynamic networks analysis to study the emergence of mutual knowledge as a percolation phenomenon

et al. 2016

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The emergence of mutual knowledge is a major cognitive mechanism for the robustness of complex socio technical systems. It has been extensively studied from an ethnomethodological point of view and empirically reproduced by multi agent simulations. Whilst such simulations have been used to design real work settings the underlying theoretical grounding for the process is vague. The aim of this paper is to investigate whether the emergence of mutual knowledge (MK) in a group of colocated individuals can be explained as a percolation phenomenon. The followed methodology consists in coupling agent-based simulation with dynamic networks analysis to study information propagation phenomena: after using an agent-based simulation we generated and then analysed its traces as networks where agents met and exchanged knowledge. Deep analysis of the resulting networks clearly shows that the emergence of MK is comparable to a percolation process. We specifically focus on how changes at the microscopic level in our agent based simulator affect percolation and robustness. These results therefore provides theoretical basis for the analysis of social organizations.

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Section: Introductionmentioning

confidence: 99%