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International audience; When studying the interbank money market (IMM), it is common to model banks as agents interacting through loans to tackle its complexity. However, the use of agent abstraction in the IMM is mostly limited to some specific cases. Besides, recent advancements show that it is promising to use blockchain technology to improve its security in a decentralized way. Based on this observation, this paper proposes an agent-oriented, blockchain-based design of the IMM trading systems, where the main objective is to decide on the times and methods of liquidity supply and demand by various market players based on what has been learned from the information available. The models in this paper are suitable for use by both academics and practitioners in this field.

International audience; Pedestrians will increasingly have to share their space with autonomous vehicles (AVs), at pedestrian crossings, and in urban shared spaces where segregation between pedestrians and vehicles is minimized. This article proposes an integrative framework to analyze pedestrian behavior in shared spaces with AVs. Following the "perception-cognition-action" cycle, the proposed framework breaks down pedestrian behavior into 3 parts: 1. Sensation and Perception; 2. Emotion and Cognition; 3. Action and Communication. The framework is used to review and synthesize current knowledge on pedestrian behavior in urban shared spaces. Studies involving pedestrians in shared environments with AVs are limited. Since an AV can be seen as a hybrid of a conventional car and a mobile robot, this review includes studies on pedestrian behavior with conventional cars and with mobile robots as well as with AVs. Examining pedestrian behavior in these three situations of interaction allows us to make assumptions about how humans will behave in sharing their urban spaces with AVs. The reviewed interactions reveal that pedestrians have diverse and imperfect behaviors. AVs must consider this variety of behaviors and follow socially compliant rules in order to be understood and accepted by pedestrians. Perspectives for AVs in shared spaces and research directions are also identified.

International audience; The nature of the social relationship within a pedestrian group influences the group's structure and behavior and thus its entitativity (i.e. the perception of a group as a unit by other pedestrians). However, existing crowd models ignore the diversity of social relationships and have limitations in reproducing group avoidance behaviors. The proposed model is an adaptation of the social force model that addresses group social relationships. The approach is calibrated by comparing the distances and angles between members of the simulated groups with observations in real crowds. Results show that intra-group distances are a key factor in collision avoidance behavior. Simulation of collision avoidance shows that group members behavior fits better with empirical data than the original model and that individuals avoid splitting groups. By simply tuning the distribution of social relationships in the simulated crowd, the model can be used to reproduce crowd behaviors in several contexts.

International audience; The Social Force Model (SFM) successfully reproduces many collective phenomena in evacuations or dense crowds. However, pedestrians behaviour is context dependent and the SFM has some limitations when simulating crowds in an open environment under normal conditions. Specifically, in an urban public square pedestrians tend to expand their personal space and try to avoid dense areas to reduce the risk of collision. Based on the SFM, the proposed model splits the perception of pedestrians into a large perception zone and a restricted frontal zone to which they pay more attention. Through their perceptions, the agents estimate the crowd density and dynamically adapt their personal space. Finally, the original social force is tuned to reflect pedestrians preference of avoiding dense areas by turning rather than slowing down as long as there is enough space. Simulation results show that in the considered context the proposed approach produces more realistic behaviours than the original SFM. The simulated crowd is less dense with the same number of pedestrians and less collisions occur, which better fits the observations of sparse crowds in an open place under normal conditions.

International audience; Navigating in complex and highly dynamic environments such as crowds is still a major challenge for autonomous vehicle such as autonomous wheelchairs or even autonomous cars. This article presents a new way of navigating in crowds by using behavioral clustering for the surrounding agents and representing the crowd as a set of moving polygons. Once the environment has been modelled in this way and the robot has all the information it needs, we then propose a navigation algorithm that is able to guide the vehicle through the scene. The key-points of this algorithm are that (1) it can avoid densely-populated areas in order to minimize the risk of being on a collision course with any of the surrounding dynamic obstacles, (2) it generates socially compliant trajectories.

Human behaviour during crisis evacuations is social in nature. In particular, social attachment theory posits that proximity of familiar people, places, objects, etc., promotes calm and a feeling of safety, while their absence triggers panic or flight. In closely bonded groups such as families, members seek each other and evacuate as one. This makes attachment bonds necessary in the development of realistic models of mobility during crises. This article presents a review of evacuation behaviour, theories on social attachment, crisis mobility, and agent-based models. It was found that social attachment influences mobility in the different stages of evacuation (pre, during and post). Based on these findings, a multi-agent model of mobility during seismic crises (SOLACE) is being developed, and it is implemented using the belief, desire and intention (BDI) agent architecture.

International audience; Many companies have a suite of digital tools, such as Enterprise Social Networks, conferencing and document sharing software, and email, to facilitate collaboration among employees. During, or at the end of a collaboration, documents are often produced. People who were not involved in the initial collaboration often have difficulties understanding parts of its content because they are lacking the overall context. We argue there is valuable contextual and collaborative knowledge contained in these tools (content and use) that can be used to understand the document. Our goal is to rebuild the conversations that took place over a messaging service and their links with a digital conferencing tool during document production. The novelty in our approach is to combine several conversation-threading methods to identify interesting links between distinct conversations. Specifically we combine header-field information with social, temporal and semantic proximities. Our findings suggest the messaging service and conferencing tool are used in a complementary way. The primary results confirm that combining different conversation threading approaches is efficient to detect and construct conversation threads from distinct digital conversations concerning the same document.

International audience; Hybrid clouds are increasingly used to outsource non-critical applications to public clouds. However, the main challenge within such environments, is to ensure a cost-efficient distribution of the systems between the resources that are on/off premises. For Multi Agent Systems (MAS), this challenge is deepened due to irregular workload progress and intensive communication between the agents, which may result in high computing and data transfer costs. Thus, in this paper we propose a generic framework for adaptive cost-efficient deployment of MAS with a special focus on hybrid clouds. The framework is based mainly on the use of a performance evaluation process that consists of simulating various partitioning options to estimate and optimize the overall deployment costs. Further, to cope with the irregular workload changes within a MAS and dynamically adapt its initial deployment, we propose an extended version of the Fiduccia-Mattheyses algorithm (E-FM). The experimental results highlight the efficiency of E-FM and show that an efficient MAS deployment to hybrid clouds depends on various factors such as the cloud providers and their different cost-models, the network state, the used partitioning algorithm, and the initial deployment.

International audience; The theory of social attachment states that individuals seek the proximity of attachment figures (e.g. family members, friends, colleagues, familiar places or objects) when faced with threat. During disasters, this means that family members may seek each other before evacuating, gather personal property before heading to familiar exits and places, or follow groups/crowds, etc. This hard-wired human tendency should be considered in the assessment of risk and the formulation of disaster management plans. Doing so may result in more realistic evacuation procedures and may minimise the number of casualties and injuries. In this context, a dynamic spatio-temporal analysis of seismic risk is presented here using SOLACE, a multi-agent model of pedestrian behaviour based on the theory of social attachment applied using the Belief-Desire-Intention approach. The model focuses on the influence of human, social, physical and temporal factors on successful evacuation. Human factors considered include perception and mobility defined by age. Social factors are defined by attachment bonds, social groups, population distribution, and cultural norms. Physical factors refer to the location of the epicentre of the earthquake, the spatial distribution/layout and attributes of environmental objects such as buildings, roads, barriers (cars), placement of safe areas, evacuation routes, and the resulting debris/damage from the earthquake. Experiments tested the influence of time of the day, the presence of disabled persons and earthquake intensity. Initial results show that factors that influence arrivals in safe areas include (a) human factors (age, disability, speed), (b) pre-evacuation behaviours, (c) perception distance (social attachment, time of day), (d) social interaction during evacuation, and (e) physical and spatial aspects, such as limitations imposed by debris (damage), and the distance to safe areas. To validate the results, scenarios have to be designed with stakeholders, who would also take part in the definition of a serious game. The recommendation of this research is that both social and physical aspects must be considered when defining vulnerability in risk analysis.

International audience; This paper describes the origins and progress of an international project to advance disaster eHealth (DEH)-the application of eHealth technologies to enhance the delivery of healthcare in disasters. The study to date has focused on two major themes; the role of DEH in facilitating inter-agency communication in disaster situations, and the fundamental need to promote awareness of DEH in the education of disaster managers and health professionals. The paper deals mainly with ongoing research on the second of these themes, surveying the current provision of disaster medicine education, the design considerations for a DEH programme for health professionals, the key curriculum topics, and the optimal delivery mode.

Les rapports de recherche du LIG - ISSN : 2105-0422RR-LIG-53; In this article we address the notion of social cohesion as being the dynamic result of interlea-ving several factors : emotions, mutual knowledge , and institutional rules. We focus on the particular context of crisis situations where the foundations of social cohesion are shaken and new, unforeseen forms of social cohesion can emerge. We aim to design a MAS that integrates these 3 factors in order to study this complex dynamic. Their differences raise difficult modelling problems, and their integration in a unified model has rarely been discussed. Drawing upon previous disjoint models, we combine these 3 factors of social cohesion into a single agent-based model. This model will be integrated into simulation tools in order to support decision-making for crisis managers.; Nous abordons dans cet article la question de la cohésion sociale comme une dynamique résultant de l'entrelacement entre plusieurs facteurs : émotions, connaissances mutuelles, et règles institutionnelles. Nous nous plaçons dans le contexte particulier des situations de crise dans lesquelles les fondements de la cohésion sociale peuvent se trouver ébranlés ; des formes nouvelles, non prévues de cohésion peuvent émerger. Notre perspective est de concevoir un SMA intégrant ces facteurs afin d'étudier cette dynamique complexe. Leurs différences sou-lèvent des problèmes difficiles de modélisation, et leur combinaison a encore été peu abordée. C'est l'objectif de cet article, où nous tirons parti de travaux antérieurs et disjoints pour proposer une intégration de ces 3 facteurs de cohésion au sein d'un modèle unifié d'agent. Ce modèle pourra alors être intégré dans des outils de simulation, afin d'être support à la décision pour les gestionnaires de crise.

Each summer in Australia, bushfires burn many hectares of forest, causing deaths, injuries, and destroying property. Agent-based simulation is a powerful tool for decision-makers to explore different strategies for managing such crisis, testing them on a simulated population; but valid results require realistic underlying models. It is therefore essential to be able to compare models using different architectures to represent the human behaviour, on objective and subjective criteria. In this paper we describe two simulations of the Australian population’s behaviour in bushfires: one with a finite-state machine architecture; one with a BDI architecture. We then compare these two models with respect to a number of criteria.

International audience; Good communication is essential within teams dealing with emergency situations. In this paper we look at communications within a resuscitation team performing cardio-pulmonary resuscitation. Communication underpins efficient collaboration, joint coordination of work, and helps to construct a mutual awareness of the situation. Poor communication wastes valuable time and can ultimately lead to life-threatening mistakes. Although training sessions frequently focus on medical knowledge and procedures, soft skills, such as communication receive less attention. This paper analyses communication problems in the case of CPR and proposes an architecture that merges a situation awareness model and the belief-desire-intention (BDI) approach in multi-agent systems. The architecture forms the basis of an agent-based simulator used to assess communication protocols in CPR teams.

International audience; This paper describes an agent based approach for simulating the control of an air pollution crisis. A Gaussian Plum air pollution dispersion model (GPD) is combined with an Artificial Neural Network (ANN) to predict the concentration levels of three different air pollutants. The two models (GPM and ANN) are integrated with a MAS (multi-agent system). The MAS models pollutant sources controllers and air pollution monitoring agencies as software agents. The population of agents cooperates with each other in order to reduce their emissions and control the air pollution. Leaks or natural sources of pollution are modelled as uncontrolled sources. A cooperation strategy is simulated and its impact on air pollution evolution is assessed and compared. The simulation scenario is built using data about Annaba (a city in NorthEast Algeria). The simulation helps to compare and assess the efficiency of policies to control air pollution during crises, and takes in to account uncontrolled sources.

International audience; In the recent years, surveys and studies have established the importance of occupant's behaviour on energy consumption in buildings. Therefore, inclusion of in-habitants' behaviours is compulsory for the assessment of building energy management system's (BEMS) strategies, which highly depends on human behaviour. The purpose of modelling the inhabitants behaviour is to see how their choices and control of household appliances can impact the energy consumption. In this paper, a co-simulation approach is presented where the inhabitants' behaviours are co-simulated with the SIMBAD-MOZART thermal model of a reference house and BEMS. The realization of all the different kinds of inhabitant behaviours into energy co-simulations will help to improve the smart grid technology and hence provide inhabitants with better services to save energy and cost while maintaining their comfort levels.

Scalability is a key issue for Multi-Agent Systems (MAS) that aim to model and simulate complex systems. Distributed infrastructures such as clusters, grids and clouds are powerful computational environments that can be effectively used to run large-scale agent-based simulations. To properly distribute an agent-based system and ensure its performance, an appropriate partitioning approach is required. Although multiple partition methods for distributed MAS exist, they remain specific to the individual requirements of a given application domain. There is no generic approach for guiding the designers and developers to select an appropriate approach for partitioning a given agent-based system. Thus a recurrent challenging task, for MAS designers and developers, is how to evaluate, select and then apply the appropriate partitioning mechanism for a given MAS. Therefore, in this paper, we present a generic conceptual framework useful to analyze existing partitioning methods. It can also be used as a basis while designing a distributed architecture of new MAS.

International audience

Environmental issues, specifically pollution are considered as major concerns in many cities in the world. They have a direct influence on our health and quality of life. The use of computers models can help to forecast the impact of human activities on ecosystem equilibrium. We are interested in the use of MAS (Multi-Agent System) for modelling and simulating the environmental issues related to pollution. In this paper, we present a review of recent studies using a MAS approach for designing environmental pollution simulation models. Interactions between the three components of the environmental problem (Social, Economic and Ecological) are presented. On the light of these interactions, studies published from 2009 to 2013 are reviewed. Models are presented in terms of: model’s purpose, studied variables, used data, representation of space and time, decision-making mechanism and implementation.

This study aims at developing a generic model of crisis mobility based on two case studies in Lebanon and Argentina. The research is characterised by a strong interdisciplinary cooperation between geographers, psychologists and computer scientists. The objective of the model is to show how appropriate human behaviours can reduce fatalities. The paper presents the methodology used in both case studies, some results of the Lebanese model as well as lessons from Lebanon to be applied to Argentinian study (on-going work). The methodology consists in field studies, model design, development, validation/calibration and simulation. The simulation aims at reproducing survey results as well as investigating new scenarios.

Published version of a chapter in the book: Recent Trends in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-38577-3_7 Managing the uncertainties that arise in disasters – such as ship fire – can be extremely challenging. Previous work has typically focused either on modeling crowd behavior or hazard dynamics, targeting fully known environments. However, when a disaster strikes, uncertainty about the nature, extent and further development of the hazard is the rule rather than the exception. Additionally, crowd and hazard dynamics are both intertwined and uncertain, making evacuation planning extremely difficult. To address this challenge, we propose a novel spatio-temporal probabilistic model that integrates crowd with hazard dynamics, using a ship fire as a proof-of-concept scenario. The model is realized as a dynamic Bayesian network (DBN), supporting distinct kinds of crowd evacuation behavior – both descriptive and normative (optimal). Descriptive modeling is based on studies of physical fire models, crowd psychology models, and corresponding flow models, while we identify optimal behavior using Ant-Based Colony Optimization (ACO). Simulation results demonstrate that the DNB model allows us to track and forecast the movement of people until they escape, as the hazard develops from time step to time step. Furthermore, the ACO provides safe paths, dynamically responding to current threats.

International audience; This paper presents a research in progress that aims to design and develop a web-based shared environment for stakeholders involved in disaster management. The goal of this environment is two-fold. Firstly it will provide a reliable disaster information source to facilitate the exchange and the analysis of previous crisis information. Secondly, it will assimilate best practices and provide recommendations based on experiences from previous disasters. One of the first steps towards such an environment is to elaborate a common and generic disaster model. This model is also a reference to define a template for the case base of previous disasters. In order for our system to provide recommendations based on previous practices, we combine case based reasoning with process mining. This article presents the first step towards a disaster management decision support system, specifically providing guidance on how to integrate process mining in the case based reasoning cycle.

International audience; Energy waste due to inhabitants' behaviour in residential buildings has emerged as a potential research area due to the increasing worldwide population and growing energy needs. However, existing approaches for simulating energy consumption are mainly limited to office buildings and are based on static profiles. In this paper we propose a 4-step co-simulation methodology to assess how inhabitants' interactions with household appliances affect energy consumption. The approach is validated using a case study showing how human activities influence the energy consumption patterns of a refrigerator. The fridge was specifically chosen because it is a high energy-consuming appliance that is strongly affected by inhabitants' behaviours. In addition, modelling the fridge is nontrivial, and in choosing this appliance we show that it is possible to apply the approach to less complex appliances. A co-simulation approach is adopted with the fridge being physically modelled in Matlab and with human behaviour being modelled in the Brahms language and simulation environment. The consumption distribution from the simulated scenario is compared with the actual distribution (using data from a consumption database), to find optimum values of tuning parameters with less than 10% variation. This methodology enables us to simulate how human behaviours affect energy appliance consumption.

International audience; The overwhelming humanitarian impact of the January 2010 Earthquake in Haiti created a tremendous coordination challenge for the humanitarian relief agencies. In this paper, we first describe the coordination mechanisms that are implemented by the United Nations and the role of its Office for the Coordination of Humanitarian Affairs (OCHA). We introduce the cluster approach, which is instrumental in providing a more efficient and effective coordination in affected disaster areas. The main thrust of our paper is on the role and use of information management (IM) in these coordination efforts. To understand better the benefits and problems of information systems, we conducted interviews with experienced information managers who participated in the Haiti relief effort. While the interviewees saw clear benefits of IM for the coordination of humanitarian relief, concerns related to information overload, reliability and accountability were found to impede the realisation of the full potential of IM.

International audience; This work consists of integrating programming paradigms such as multi-agent systems and rule-based reasoning into a multimedia creation and display platform for interactive artistic creation. It has been developed in order to allow artists to build dynamic and interactive exhibitions based on pictures and sounds and featuring self-evolving and autonomous configurations.

International audience; Creativity is an important activity in many professional and leisure domains. This article presents a first step towards a system which will provide a set of tools for enhancing the individual creative abilities of the user in a design task. We have identified aspects which are characterise individual creativity: motivation, domain knowledge, externalization, inspiration and analogies, and requirements handling. Based on these aspects we have defined requirements and suggest associated system functionalities.

International audience; Training firefighters is a difficult process in which emotions and nonverbal behaviors play an important role. The authors have developed a mixed reality environment for training a small group of firefighters, which takes into account these aspects. The assessment of the environment was made up of three phases: assessing the virtual agents to gauge their expressiveness, assessing the contextual virtual environment to see if it provides the same decision-making support as that found in the real world, and verifying indexicality to support agent interaction.

In the near future, autonomous vehicles will have to navigate in dense and dynamic urban environments like shared spaces. In such spaces, segregation between pedestrians and vehicles is minimized and users must negotiate their passage without explicit traffic rules. Pedestrians navigate following some social norms and they expect the autonomous vehicle to navigate safely, efficiently and in accordance with the social and urban conventions. To achieve this, a key element of AV navigation in shared spaces is understanding and anticipating pedestrian behaviors and their interactions.However, we do not know yet how pedestrians will behave, because it is still very uncommon for pedestrians to share their space with autonomous vehicles. Our research problem is the following: how to anticipate pedestrian behaviors in a space shared with an autonomous vehicle?This thesis is part of the ANR project HIANIC (Human Inspired Autonomous Navigation In Crowds). In this thesis, we study the behavior of pedestrians in a shared space with an autonomous vehicle by modeling and simulating realistic pedestrian behavior.Our approach integrates empirical observations and concepts from social science into an agent-based model and simulator for an application in robotics. At each step, the proposed model has been evaluated and validated through simulations of many scenarios and comparisons with real-world data.Our first contribution is an agent-based model for individual pedestrian behavior in a shared space context. The model takes into account pedestrians' perception, attention and personal space in order to simulate sparse crowds in open environments.Our second contribution is an agent-based model for pedestrian groups with four social relationships (couples, friends, families and work colleagues). The model simulates both the movement of social groups of pedestrians in various crowd contexts and the avoidance behavior of groups by other pedestrians.Our third contribution is an agent-based model for pedestrian interaction with an autonomous vehicle in a shared space. The model allows to represent heterogeneous, accurate and explainable pedestrian behaviors in several interaction situations with an autonomous vehicle. The model can be used to reproduce real-world scenes and predict pedestrian trajectories around an autonomous vehicle in real time.Our fourth contribution is the implementation of the model in order to propose the simulator SPACiSS, "Simulator for Pedestrians and an Autonomous Car in Shared Spaces". SPACiSS is open source and can simulate interactions between pedestrians and vehicles in different shared space scenarios. With the integration in the ROS framework, commonly used in robotics, SPACiSS is designed as an environment to test autonomous navigation systems.We have shown that agent-based modeling and simulation supports the successful integration of social science and robotics. This association is promising to address real-world scenarios.; Dans un futur proche, les véhicules autonomes ne seront plus limités aux routes et auront à naviguer dans des environnements urbains denses et dynamiques comme les espaces partagés. Dans de tels espaces, la séparation entre piétons et véhicules est réduite au minimum et les usagers doivent négocier leur passage sans règles de circulation explicites. Les piétons naviguent selon certaines normes sociales et s'attendent à ce que le véhicule autonome ait une navigation sécurisée, mais aussi efficace et conforme aux conventions sociales et urbaines. Pour cela, un élément clé de la navigation dans les espaces partagés repose sur la compréhension et l'anticipation des comportements piétons et de leurs interactions.Cependant, nous ne savons pas comment les piétons vont se comporter, car actuellement il est très rare que des véhicules autonomes naviguent dans le même espace que des piétons. Notre problématique est donc la suivante : comment anticiper les comportements piétons dans un espace partagé avec un véhicule autonome ?Cette thèse s'inscrit dans le cadre du projet ANR HIANIC (Human Inspired Autonomous Navigation In Crowds). Dans cette thèse, nous étudions le comportement des piétons en espace partagé avec un véhicule autonome en modélisant et en simulant des comportements piétons réalistes.Notre approche intègre des observations empiriques et des concepts issus des sciences sociales afin de proposer un modèle et un simulateur à base d'agents pour une application en robotique. À chaque étape, le modèle proposé a été évalué et validé par des simulations de plusieurs scénarios et des comparaisons avec des données réelles.Notre première contribution est un modèle des comportements piétons individuels dans un contexte d'espace partagé. Le modèle tient compte de la perception, de l'attention et de l'espace personnel des piétons pour simuler des foules peu denses en environnement ouvert.Notre deuxième contribution est un modèle de quatre relations sociales au sein des groupes de piétons (couples, amis, familles et collègues de travail). Le modèle permet de simuler à la fois le mouvement des groupes sociaux de piétons dans plusieurs contextes de foule et les comportements d'évitement des groupes par d'autres piétons.Notre troisième contribution est un modèle des comportements piétons en interaction avec un véhicule autonome en espace partagé.Le modèle permet de représenter des comportements piétons à la fois hétérogènes, précis et explicables dans plusieurs situations d'interaction. Le modèle peut être utilisé pour reproduire des scènes du monde réel et pour prédire les trajectoires des piétons autour d’un véhicule autonome en temps réel.Notre quatrième contribution est l'implémentation du modèle pour proposer le simulateur SPACiSS, "Simulator for Pedestrians and an Autonomous Car in Shared Spaces". SPACiSS est open source et permet de simuler les interactions entre les piétons et les véhicules dans différents espaces partagés. Avec l'intégration dans le cadre ROS, couramment utilisé en robotique, SPACiSS est conçu comme un environnement pour le test de systèmes de navigation autonome.Nous avons montré que la modélisation et la simulation à base d'agents peuvent contribuer à une intégration efficace entre les sciences sociales et la robotique. Cette association est prometteuse pour aborder des scénarios du monde réel.

Evacuations are necessary during earthquake crisis to mitigate and avoid risks of exposure to hazards that can cause injury or death. Evacuation are social in nature. This is mainly because the main agents in evacuations are people who possess highly evolved social strategies for coping with danger. Social attachment theory posits that proximity seeking behaviours are activated during danger. In this situation people seek attachment figures. Attachment figures include familiar people, places, object, etc. The presence of attachment figures promotes the feeling of calm and safety. Conversely, their absence result in anxiety and flight. This means for example that during disasters individuals may seek family members, before evacuating. Also, this explains the behaviour why people gather personal property before heading to familiar exits and places, or follow groups/crowds, etc.In this framework, a multidisciplinary approach – based on social, geoscience, spatial and computer sciences – is proposed to simulate individuals’ behaviours after an earthquake in the city of Grenoble, France. For this purpose, SOLACE, a multi agent model on crisis evacuations was developed to answer eight key questions (Q1 to Q8) that can explain the nature and impact of human evacuation behaviour modulated by social attachment. The effect of several parameters on the number of arrivals in safe areas was observed: social attachment (Q1); knowledge (Q2); number of close bonds (Q3); time of day (Q4); presence of disability (Q5); presence of casualties (Q6); earthquake intensity (Q7); and radius of danger zones around buildings (Q8).The results of the experiments point to the importance of social interactions during evacuations. The behaviours of individuals are significantly affected by their social environment that responds to the challenges imposed by the physical environment produced by earthquake disasters. The capacity and tendency for social interaction are inherent in humans and need to be considered in evacuations. It was shown that social attachment is important because it can facilitate saving more lives during earthquake disasters.The first and main contribution of the research is to add to arguments stressing the importance of human behaviour and the social dynamics that emerge during crisis evacuations. The second major contribution of the study is SOLACE, the multi agent-based model for earthquake evacuation implemented using social attachment. The third major contribution is that the research supports the benefit of using accurate spatial data in dynamic multi agent-based models.; L’évacuation des populations est nécessaire pendant les crises sismiques afin d'atténuer et d'éviter l'exposition à des dangers qui peuvent causer des blessures ou la mort. Tout comme le risque, l’évacuation est de nature sociale. Cela s'explique principalement par le fait que les personnes qui évacuent possèdent des stratégies sociales très évoluées pour faire face au danger. La théorie de l'attachement social suppose que la recherche de personnes ou de lieux familiers est réalisée en situation de danger. Dans cette situation, les gens recherchent des figures d'attachement. Les figures d'attachement comprennent des personnes, des lieux, des objets familiers, etc. La présence de figures d'attachement favorise le sentiment de calme et de sécurité. Inversement, leur absence entraîne l'anxiété et la fuite. Cela signifie, par exemple, qu'en cas de catastrophe, les personnes peuvent chercher des membres de leur famille avant d'évacuer. Cela explique aussi pourquoi les gens recueillent des biens personnels avant de se diriger vers des sorties et des endroits familiers, ou de suivre des groupes ou des foules, etc.Dans ce contexte, une recherche pluridisciplinaire a été menée, basée sur les apports des sciences sociales, de la terre, de l’information spatiale et de l’informatique, pour simuler les comportements des individus à la suite d’un séisme dans la ville de Grenoble (France). Dans cette optique, SOLACE, un modèle multi-agents sur les évacuations de crise, a nous avons développé pour répondre à huit questions clés (Q1 à Q8) qui peuvent expliquer la nature et l'impact des comportements d'évacuation humaine modulés par les liens sociaux. L'effet de plusieurs paramètres sur le nombre d'arrivées dans les zones sûres a nous avons observé: il s’agit de l'attachement social (Q1), des connaissances (Q2), du nombre de liens étroits (Q3), de l'heure de la journée (Q4), de la présence d'un handicap (Q5), de la présence de victimes (Q6), de l'intensité du séisme (Q7) et du rayon des zones dangereuses autour des bâtiments (Q8).Les résultats des expériences montrent l'importance des interactions sociales pendant les évacuations. Les comportements des individus sont fortement influencés par leur environnement social qui répond aux défis imposés par l'environnement physique produit par les catastrophes sismiques. La capacité et la tendance à l'interaction sociale sont inhérentes aux humains et doivent être prises en compte dans les évacuations. Nous avons démontré que l'attachement social est important parce qu'il peut faciliter le sauvetage d'un plus grand nombre de vies lors de catastrophes sismiques.La première et principale contribution de la recherche est d’appuyer les arguments soulignant l'importance du comportement humain et des dynamiques sociales qui émergent lors des évacuations de crise. La deuxième contribution majeure de l'étude est SOLACE, le modèle multi-agents d'évacuation en cas de tremblements de terre mis en œuvre en utilisant l'attachement social. La troisième contribution majeure est que la recherche confirme l'avantage d'utiliser des données spatiales précises dans des modèles dynamiques multi-agents.

We discuss in this thesis about designing an computer system for an evaluative support , to support and evaluate in real-time the collaborative activity in the particular case of "an activity governed by processes from different organizations". We define a process as a set of rules, policies, plans, standards which aim to guide and be a reference for the realization of a collaborative activity. Our research is applied to training in crisis management, and situated in the technological context of tangible interaction.To implement a flexible and comprehensible evaluative support, we propose a socio-technical systemfor bringing the actors shared and distributed organizational consciousness.In this context, three key issues are considered: (1) representation and management of the contexts associated with the sustained activity and the interactions between the involved stakeholders, (2) representation and management of various processes associated with the sustained activity and the interaction and (3) the articulation between the sustained activity and the interaction.To answer these issues, we offer the OrA system based on three groups of principles, both about sutained activiy and interaction : modularity and representation of processes and contexts, autonomous management and loosely coupled processes and contextual elements, flexible coordination between these process and context management mechanisms.These principles are implemented in a computer system based on the model of groupware, especially CLOVER, a traces models, and normative multi-agent systems.This system is evaluated by demonstrating the ability to model the process of a practical case of crisis management exercise, and by providing a use situation of a real exercise training in crisis management.; Nous abordons dans cette thèse le problème de la conception d’un système informatique de soutien évaluatif, pour soutenir et évaluer en temps réel l’activité collaborative dans le cas particulier "d'une activité régie par des process issus d'organisations différentes". Nous définissons un process comme un ensemble de règles, de politiques, de plans, de normes ayant pour vocation de guider et de servir de référence à la réalisation d’une activité collaborative. Nous positionnons notre recherche dans le cadre applicatif de l’entrainement à la gestion de crise, et dans le cadre technologique de l’interaction tangible.Pour mettre en place un soutien évaluatif flexible et intelligible, nous proposons un système socio-technique capable d’apporter aux acteurs une conscience organisationnelle partagée et distribuée.Dans ce cadre, trois verrous essentiels sont considérés : (1) représentation et gestion de contextes liés à l’activité soutenue et aux interactions entre acteurs, (2) représentation et gestion des différents process liés à l’activité soutenue et à l’interaction, et (3) articulation entre l'activité soutenue et l'interaction.Pour répondre à ces verrous, nous proposons le système OrA s’appuyant sur trois groupes de principes relatif à l'activité soutenue et à l’interaction : modularité et représentation des process et contextes, gestion autonome et faiblement couplée des process et des éléments de contexte, coordination flexible entre ces mécanismes de gestion de process et de contextes.Ces principes sont mis en oeuvre au sein d’un système informatique s’appuyant sur les modèles des collecticiels, et en particulier CLOVER, des modèles de traces, des systèmes multi-agents normatifs.Ce système est évalué en démontrant la possibilité de modéliser les process d’un cas pratique d’exercice de gestion de crise, puis en proposant une utilisation en situation d’un exercice réel d’entrainement à la gestion de crise.

Energy consumption in buildings is affected by various factors including its physical characteristics, the appliances inside, and the outdoor environment, etc. However, inhabitants’ behaviour that determines the global energy consumption must not be forgotten. In most of the previous works and simulation tools, human behaviour is modelled as occupancy profiles. In this thesis the focus is more on detailed behaviour representation, particularly the cognitive, reactive, and deliberative mechanisms. The inhabitants’ dynamic behaviour is modelled and co-simulated together with the physical aspects of a building and an energy management system. The analysis of different household appliances has revealed that energy consumption patterns are highly associated with inhabitants’ behaviours. Data analysis of inhabitants’ actions and appliances’ consumptions is used to derive a model of inhabitants’ behaviour that impacts the energy consumption. This model represents the cognitive mechanisms that provide causes that motivate the actions, including the communication with other inhabitants. An approach based on multi-agent systems is developed along with a methodology for parameter tuning in the proposed behaviour model. These tools are used to co-simulate, not only the physical characteristics of the building, the reactive behaviour that is sensitive to physical data, and deliberative behaviour of the inhabitants, but also the building energy management system. The energy management system allows the direct adjustment of the building parameters or simply giving advice to the inhabitants. The impact of different types of inhabitants’ behaviours, with and without the inclusion of an energy management system is analyzed. This work opens new perspectives not only in the building simulation and in the validation of energy management systems but also in the representation of buildings in the smart grid where signals can be sent to end users advising them to modulate their consumption., La consommation énergétique dans le secteur bâtiment dépend de diverses facteurs parmi lesquels ses caractéristiques physique, ses équipements, l’environnement extérieur, etc… mais il ne faut pas oublier le comportement des habitants qui est déterminant pour la consommation énergétique globale. Or, la plupart des travaux et outils représentent les occupants par des profils d’occupation. Cette thèse s’intéresse à la représentation plus détaillée du comportement des occupants, en particulier les mécanismes cognitifs, réactifs et délibératifs. Le comportement dynamique des occupants est modélisé et co-simulé avec les aspects physiques et des éventuels systèmes de gestion énergétique. L’analyse de la consommation de différents équipements électroménagers met en évidence que le consommation énergétique est très dépendante des comportements des occupants. L’analyse des consommations et des actions des habitants permet d’élaborer un modèle du comportement des occupants impactant la consommation énergétique. Le modèle représente des mécanismes cognitifs, qui représente les causes qui motivent les actions, incluant des échange avec d’autres acteurs humains. Une approche à base d’agents logiciels a été développée. Outre les aspects techniques, une méthodologie de réglage des paramètres des modèles de comportement est proposée. Ces outils sont utilisés pour réaliser une co-simulation représentant la physique du bâtiment, le comportement réactif, c’est-à-dire sensible aux données physiques, et délibératif des habitants mais aussi un système de gestion énergétique qui peut ajuster directement la configuration du logement ou simplement conseiller ces occupants. L’impact de différents types de comportements, avec et sans gestionnaire énergétique est analysé. Ces travaux ouvrent de nouvelles perspectives dans la simulation bâtiment, dans la validation de gestionnaires énergétiques mais aussi dans la représentation des bâtiments dans les réseaux d’énergie dits intelligents, dans lesquels des signaux peuvent être envoyés aux utilisateurs finaux pour les inviter à moduler leur consommation.

International audience; We propose a normative approach to collaborative support system design in distributed tangible environments. Based on activity theory, our goal is to mediate rather than drive human activity and to integrate components from the physical, numerical and social environments. We propose an original architecture coupling a physical space (tools supporting human activity), a processing space (agent performing activity, be it human or artificial), an informational space (traces reflecting activity), and a normative space (filters regulating activity). We further consider collaboration as a conversational process grounded in the objects of the working space. To this end, tangible objects of various kinds are designed to support multi-threaded activity. Heterogeneous trace properties may then be fused to situate activity and ground the filtering process. Interface agents are designed to provide appropriate visual feedback and support mutual awareness. Beyond the mere sharing of individual or group activity, we approach awareness as involving mutual knowledge of the activity constraints. We show through simple examples from the RISK game the potential richness of the proposed approach.