Résumé

Résumé

Information security mechanisms are crucial for Vehicular Ad-hoc NETworks (VANET) applications in order to preserve their robustness. The efficiency of these applications relies on the reliability of the used information, especially the vehicle-related information such as location and speed. Trust management models are crucial to evaluate the quality of the used information. Accordingly, we focus in this paper on the assessment of speed information to detect the malicious vehicles using a fuzzy-based model (SP-TRUST). The proposed model relies on two fuzzy inference systems. The first one evaluates the speed trust based on traffic rules (inter-vehicle distance) while considering the road topology (angle deviation) and the traffic state (density). The correlation between these parameters and the speed value is assessed. The second inference system assesses the speed trust based on the behavior of neighbor vehicles using the median speed of vehicles. Simulations were carried out to evaluate the robustness and the scalability of SP-TRUST model. The results of the experimental studies proved that the model performs well in detecting different behaviors of malicious vehicles in different scenarios, especially when the percentage of malicious vehicles is lower than 50%.

Résumé

The paradigm of Social Internet of Things (SIoT) incorporates the concepts of social networking in the Internet of Things (IoT). The idea of SIoT is to allow objects to autonomously establish social relationships, which may facilitate network navigability and the discovery of information and services. The characteristics of the IoT such as the heterogeneity and the dynamicity of the network and the social relationships between devices lead to several challenges including how to build a reliable network. In this paper, we propose an adaptive trust management model that helps nodes seeking trusted service providers. The trustworthiness of a service provider is assessed on the basis of its past experiences with the requestor and of the recommendations of the requester’s neighbors. In our trust model, the trust parameters evolve dynamically in response to the change of the network context, the type of the demanded service and the nature of the relationships between the different nodes. The experiment results show that our proposed model achieves high accuracy and it is proved to be resilient against common attacks.

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The rise of terrorism over the past decade did not only hinder the development of some countries, but also it continues to destroy humanity. To face this concept of an emerging crisis, every country and every citizen is responsible for the fight against terrorism. As conventional plans became useless against terrorism, governments are required to establish innovative concepts and technologies to support units in this asymmetric war. In this paper, we propose a new multi-agent model for
counter-terrorism characterized by a methodical process and a flexibility to handle different contingency scenarios. The division of labour in our multi-agent model improves decision making and the structuring of organisational plans.

Résumé

Nowadays the world is suffering from the emergence of a new concept of war, it is the asymmetric warfare created by the terrorists' new combat doctrine. As the plans to face classic enemies have become unusual against terrorism, this calls for innovative concepts and technologies to support the units and to improve the capability of leaders and structure their choices. In this paper, we propose a multi agent architecture for action planning against terrorist attacks. It is characterized by rapid decisive responses and methodical steps to handle the situation, and by the flexibility to adapt a contingency scenario. We aim to create a multi-agent model that describes the relation between actors during the terrorist attack in order to find the best possible units distribution to neutralize the enemy.

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Emotions in workplace is a topic that has increasingly at
tracted attention of both organizational practitioners and academics. This is due to the fundamental role emotions play in shaping human resources behaviors, performance, productivity, interpersonal relationships and engagement at work. In the current research, a computational social simulation approach is adopted to replicate and study the emotional experiences of employees in organizations. More speci cally, an emotional
agent-based model of an employee at work is proposed. The developed model is used in a computer simulator WEMOS (Workers EMotions in Organizations Simulator) to conduct certain analyzes in relation to the most likely emotions-evoking stimuli as well as the emotional content of several work-related stimuli. Simulation results can be employed to gain deeper understanding about emotions in the work life.

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Crises are complex situations due to the dynamism of the environment, its unpredictability and the complexity of the interactions among several different and autonomous involved organisations. In such a context, establishing an organisational view as well as structuring organisations’ communications and their functioning is a crucial requirement. In this article, we propose a multi-agent organisational model (OM) to abstract, simulate and analyse a crisis management system (CMS). The objective is to evaluate the CMS from an organisational view, to assess its strength as well as its weakness and to provide deciders with some recommendations for a more flexible and reactive CMS. The proposed OM is illustrated through a real case study: a snowstorm in a Tunisian region. More precisely, we made the following contribution: firstly, we provide an environmental model that identifies the concepts involved in the crisis. Then, we define a role model that copes with the involved actors. In addition, we specify the organisational structure and the interaction model that rule communications and structure actors’ functioning. Those models, built following the GAIA methodology, abstract the CMS from an organisational perspective. Finally, we implemented a customisable multi-agent simulator based on the  Janus  platform to analyse, through several performed simulations, the organisational model

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Emotion mechanisms represent an important moderating factor of human behavior. Thus, they are necessary to produce realistic behavioral simulations. This work addresses this challenging issue by incorporating emotional processes into an agent model. We intend to show the potential of emotions and coping mechanisms to produce fast and human-like emotional behaviors, particularly, in emergency situations. We focus on the interplay of emotions and goals and its impact on agent behavior. Emotions constitute heuristics to agent decision making. They induce emotion-specific goals that orient agent goal adoption mechanisms and fasten its behavior selection.

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Emotions shape human behaviors particularly during stressful situations. This paper addresses this challenging issue by incorporating coping mechanisms into an emotional agent. Indeed, coping refers to cognitive and behavioral efforts employed by humans to overcome stressful situations. In our proposal, we intend to show the potential of the integration of coping strategies to produce fast and human-like behavioral responses in emergency situations. Particularly, we propose a coping model that reveals the effect of agent emotions on their action selection processes.

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Research works on human behaviour modelling and simulation
continue to increase in recent years. Indeed, emotion and personality are amongthe most important human characteristics that influence behaviour. Particularly, during emergencies, emotional dynamics have a major influence on individual
and collective behaviours. In this paper, we aim to provide an integrated review on this challenging and multidisciplinary field. We give first an overview of computational models of emotions and personalities. Then, we expose and discuss emotional and behavioural models. An emphasis is given to the role of
internal and external emotional dynamics in the production of realistic behaviours during emergencies. Internal emotional dynamics affect cognitive processes at an individual level. However, external emotional dynamics, studied through phenomena such as empathy or emotional contagion, are
essential to simulate collective emotional dynamics.

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We consider a supply chain consisting of a supplier and locations selling an innovative product. These locations could collaborate together by transshipment which is known as product transferring adopted mainly to reduce inventory costs and to improve customer service level. In this research, we are interested in the transshipment problem where the customer demands, the holding and the shortage costs are uncertain and represented by fuzzy sets. Our objectives are to propose a transshipment policy that takes into account the fuzziness of the mentioned parameters and to derive the approximate replenishment quantities. In order to achieve these objectives, we propose a transshipment decision process considering decision makers attitudes towards risks and a hybrid algorithm based on fuzzy simulation and genetic algorithm designed to determine the approximate replenishment quantities.

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Over the last decade, emotions have received considerable attention among scholars in agent oriented systems. In fact a large amount of computational models of emotions has been developed and a new generation of artificial agents has emerged to give rise to emotional agents, in particular the Emotional BDI (EBDI) agents. However, in spite of the several interesting studies that have been conducted to underline the role of emotions in decision-making, few works in the agent community have shed the light on the influences of both immediate and expected emotions to drive decision-making. In this context, we intend to propose a new conceptual model of EBDI agency that involves the interplay among immediate emotions, expected emotions and rational decisions of artificial agents.

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This paper introduces an organizational multi-agent model for crisis management. The considered crisis is a heavy snow storm, occurred at a north Tunisian delegation. The studied crisis caused severe infrastructure damages and endangered people’s lives. Crisis systems are generally made of several heterogeneous and autonomousorganizations. Each organization is given tasks and their tasks are strongly correlated. Organizations have to interact frequently and cooperate at a high level to deal with the crisis. In this context, thinking the crisis management at a macro level with an organizational view as well as structuring organizations’ communications and their functioning is a crucial requirement. Following this view, the main purpose of our work is to propose a multi-agent system organization that manages resources efficiently, structure the communication among all the actors involved in the crisis management and orchestrate their work. More precisely, we provide an environment model that identifies all concepts and entities involved in the snow storm crisis. We specify, using GAIA methodology, a multi-agent organizational model that defines the roles involved in the system and the interaction protocols to realize organizational objectives. Finally, a simulator has been implemented to demonstrate the feasibility of our approach.

Résumé

Emotions have a considerable effect on human
behaviors and cognitive processes, especially during crisis
situations. Emotion modeling is therefore a key solution to
generate realistic social simulations in crisis situations. In this
context, we intend to model human emotional dynamics and to
study their effect on individual and collective behaviors during
emergency situations. In this paper, we focus on the first part of
this research work which consists in the modeling of emotion
generation in emergency situations. Thus, we provide first a
modeling of the disaster space in a rescue simulation context.
Then, we propose a computational model of the generated
human emotions, basing on the emergency environment. This
model uses the appraisal theories of emotions.

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Emotion is one of the major factors that can affect the human behavior, especially in emergency situations. To consolidate this idea, we need to model and to simulate human emotional dynamics and their effects on the behaviors of human civilians in emergencies. This may help consequently emergency managers to better react and make decisions. This paper addresses this challenge by presenting a new emotional agent model. The final goal of this work is to build an emotional agent based simulator of civilians during an emergency situation. The paper describes first the proposed agent model, based on an appraisal theory of emotions. It provides then an implementation and experimentations performed using the RoboCupRescue project.

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This paper discusses an approach to build a multiagent system for simulating container management in a hub port logistics. The simulator has as goal to help assessing and defining container management strategies. This allows to plan and to control the management of containers while minimizing the waiting time and the parasite shifts and insuring the consistency of the performed tasks sequence. The proposed model involves the multipoint of view and the emergence of behavior specific to the theory of complex systems. The paper is structured as follows: first we present related works, then we expose the multiagent model of the simulator, after that we present the internal structure of the agents and finally we provide and discuss first implementation and results.

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We consider a distribution network composed of one supplier and several non-identical locations characterized by fuzzy customer demands and service level constraints. These locations could cooperate together via product transfer known as transshipment. The transshipment problem consists in determining the replenishment quantities that minimize the total inventory cost where a specific transfer policy is practiced. Our objectives in this paper are to identify an inter-location transfer policy that participates to satisfy the service level constraints and to determine the approximate replenishment quantities. To achieve these objectives we propose:(1) a new transshipment model based on the chance constrained programming,(2) a two-step transshipment policy that differs from classic ones by product transfer from locations in need to others also in need and (3) a hybrid algorithm based on fuzzy simulation and genetic algorithms to approximate replenishment quantities.

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Pastoral systems are considered as complex systems, given the number of entities and the multitude of interactions and levels of granularity. To conduct a study of such system taking into account the interactions and their results, analytical approaches are not adequate. In this paper, we present an agent-based model of the animal behavior in the pastoral system taking into account the selective food aspect. This model has been validated using a multi-agent based simulation implemented on the simulation platform Cormas. The obtained results reflect the importance of this aspect in the animal behavior and its effects on vegetation cover.

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This paper deals with the transshipment problem characterized by the uncertainty relative to customer demands and transfer lead time. We consider a distribution network of one supplier and N locations selling an innovative product. The customer demands and the transfer lead time are evaluated based on expert judgments and they are consequently represented by fuzzy sets. Our aims in this work are: (1) to identify a transshipment policy that takes into account the fuzziness of customer demands and transfer lead times and (2) to determine the approximate replenishment quantities which minimize the total inventory cost. In order to achieve these aims, we propose a new transshipment policy where the transshipment decision is made within the period and the possible transshipment decision moments belong to a fuzzy set. We consider the decision maker behavior types (pessimistic and optimistic) to determine the precise transshipment decision moment and the transshipment quantity. We propose a hybrid algorithm based on fuzzy simulation and genetic algorithm to approximate the optimal replenishment quantities.

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Our goal is to create a virtual consumer population that can be used for simulating the effects of marketing strategies in a competing market context. That requires having a consumers' behavioral model allowing the representation of observed individual behaviors and the simulation of a large population of consumers. That also requires finding the parameters' values characterizing the virtual population that reproduces real market evolutions. This paper proposes a consumer behavioral model based on a set of behavioral primitives such as imitation, conditioning and innovativeness, which are founded on the new concept of behavioral attitude. It shows that this model provides an interpretation of the main concepts and cognitive features, issued from marketing research and psycho-sociology works on consumption. The paper presents also the CUstomer BEhavior Simulator (CUBES), which has been realized for implementing the customer model and leading multi-agents simulations. It shows how genetic algorithms (GA), in addition to multi-agent systems, are used to fit the characteristics of the virtual consumers' population into a global realistic market behavior.

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No abstract available.

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Theoretical concepts dealing with consumer behaviour issues from studies led in various research areas: marketing, psychology, sociology and economics. This paper presents a multi-agent simulation of consumer behaviour based on an integrating approach. Our goal is to create virtual populations including several thousands of artificial consumers that exhibit realistic behaviours in the context of a competing market. These populations are used to test the effects of marketing strategies. Existing consumer behavioural models are not well suited for the realization of such market simulations including a large number of artificial consumers. In this work a consumer behavioural model based on the concept of behavioural attitude is introduced to solve this problem. It proposes to integrate and organize most of the fundamental notions elaborated within the aforementioned research areas.