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Thèse de

Omar Rihawi

mercredi 3 décembre 2014
Amphi Turing, Bât M3 - LIFL

Modelling and simulation of distributed large scale situated multi-agent systems

Mme. Zahia GUESSOUM, Maître de Conférences HDR, Université de Reims Champagne-Ardenne (Rapporteur). M. Laurent VERCOUTER, Professeur, INSA Rouen (Rapporteur). M. Gregory BONNET, Maître de Conférences, Université de Caen Basse-Normadie (Examinateur). Mme Sophie TISON, Professeur, Université Lille 1 (Examinateur). M. Philippe MATHIEU, Professeur, Université Lille 1 (Directeur). M. Yann SECQ, Maître de Conférences, Université Lille 1 (Co-directeur).

Multi-agent simulations are interesting tools to reproduce and
explain complex phenomena. These phenomena are often characterized
by an emerging behaviour at the population level that is induced
by the interaction at the individual level. When such simulations
involves a high number of agents and interactions, it becomes
intractable to execute it on a single computer.

This thesis is focused on two aspects to enable the simulation of
large scale multi-agent systems: the first one is concerned with
design choices that can be used to distribute the simulator on
a computer network, while the second one explores the relaxation
of synchronisation constraints in this distributed context.

Concerning the distribution challenge, we propose the use of two
strategies, one relying on a repartition based on agents properties
while the other is based on a division of the environment. These
two approaches have been implemented and validated through two
applications involving different emergent properties.

The second aspect is based on the hypothesis that in such large
scale systems, if some entities fails, it should not affect the
observed phenomena that is characterized at the macroscopic scale.
The type of failure that we have introduced is linked to the
relaxation of synchronization constraints by allowing computers
to progress independently in a given time window. We have studied
this relaxation and its impacts on performances and on the emerging
behaviour of two different applications exhibiting different
population dynamics.

This work has led to the design and implementation of a distributed
simulator for large scale multi-agent systems that has been
validated on a commodity computer network and on the Grid'5000
infrastructure. The largest simulation that has been tested has
involved 50 millions agents running on 50 computers.

Ours

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