Résumé

Serverless Computing, also named Function as a Service (FaaS) in the Azure cloud provider, is a new feature of cloud computing. This is another brick, after managed and fully managed services, allowing to provide on-demand services instead of provisioned resources and it is used to strengthen the company’s ability in order to master its IT system and consequently to make its business processes more profitable. Knowing that decision making is one of the important tasks in business processes, the improvement of this task was the concern of both the industry and the academy communities. Those efforts have led to several models, mainly the two Object Management Group (OMG) models: Business Process Model and Notation (BPMN) and Decision Model and Notation (DMN) in order to support this need. The DMN covers the decision-making task in business processes mainly the eligibility of business rules. This eligibility can be automated in order to help designers in the mastering of this important task by the running of an algorithm or a method such as the Multiple Criteria Decision Making (MCDM). This feature can be designed and implemented and deployed in various architectures to integrate it in existing Business Process Management Systems (BPMS). It could then improve supporting several business areas such as the Business Intelligence (BI) process. In this paper, our main contribution is the enrichment of the DMN model by the automation of the business rules eligibility through Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) using FaaS to further streamline the decision-making task in business processes. Results show to strengthen business-IT alignment and reduce the gap between the real world and associated IT solutions.

Résumé

Decision-making in Business Process is a real challenge, given its technical complexity and organizational impact. Mostly, decision-making is based on business rules fired by an inference engine using facts reflecting the context of the current process task. Focus on a task alone and in isolation from the rest of the process can easily lead to inconsistency in decision-making. In this paper, we aim to improve the importance of consistency of decision-making throughout the process. To fulfill this aim, our contribution is to propose Consistency Working Memory RETE (CWM-RETE): a Framework based on the Rete Algorithm as a pattern-matching algorithm to simulate inference; and MongoDB as a document-oriented database to serialize business rules. This framework enables the compatibility of decision-making throughout the business process. The experimentation is based on the Business Intelligence process as a case study and it is shown that the decision-making process can generate different results depending on whether consistency functionality is enabled or not.

Résumé

Recent researches on computational modeling show that emotions have a major influence on human behavior and decision making. Therefore, it is recognized that they are necessary to produce human-like in artificial agents. Several computational behavior models have been proposed. However, some of them have incorporated the emotion, others have integrated the psychological aspects in order to study the human behavior, but they did not take into account both of the emotional and the psychological impacts. In this context, we attempt to present an overview of the existent works. Then, we aim to present a new behavior agent model that integrates both of the psychological and emotional aspects to prove their impacts on the human decision.

Résumé

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.

Résumé

In this article, the multi-depot heterogeneous fleet vehicle routing problem with time window (MDHFVRPTW) is considered. The objective of this work is to minimize the total traveled distance while delivering goods to geographically dispersed customers. In our research we solved the MDHFVRPTW with a multi-agent approach based on the hybridization of three meta-heuristics which are a particle swarm optimization algorithm (PSO), a genetic algorithm (GA) and a memetic algorithm (MA). A mathematical programming model for the problem is presented. In order to show the performance of the proposed approach we tested it on different benchmarks and we compared it with other results obtained from the literature.

Résumé

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.

Résumé

This paper presents the home health care routing and scheduling problem as the vehicle routing problem with time windows (VRPTW). we propose a dynamic approach for home care planning to ensure the continuity of care for patients. The proposed approach aims to optimize the care plan route of each caregiver according to their skills, availabilities and preferences. We aim also to minimize the violation of time windows in order to maximize patient and caregiver’s satisfaction. The optimal plan route is generated with a population-based algorithm which is the Artificial Immune Algorithm (AIS). A multi-agent approach is used to ensure communication and coordination between the different actors.

Résumé

The modelling of business processes and in particular decision-making in these processes takes an important place in the quality and reliability of IT solutions. In order to define a modelling standards in this domain, the Open Management Group (OMG) has developed the Business Process Model and Notation (BPMN) and Decision Model and Notation (DMN). Currently, these two standards are a pillar of several business architecture Frameworks to support Business-IT alignment and minimize the gap between the managers expectations and delivered technical solution. In this paper, we propose the Multi-Criteria DMN (MC-DMN) which is a DMN enrichment. It allows covering the preference to criteria in decision-making using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as a Multi-Criteria Decision-Making (MCDM) method and therefore it gives more faithfulness to the real world and further agility face the business layer changes.

Résumé

Nowadays, we are confronted with increasingly complex information systems. Modelling these kinds of systems will only be controlled through appropriate tools, techniques and models. Work of the Open Management Group (OMG) in this area have resulted in the development of Business Process Model and Notation (BPMN) and Decision Model and Notation (DMN). Currently, these two standards are a pillar of various business architecture Frameworks to support Business-IT alignment and minimize the gap between the managers’ expectations and delivered technical solutions. Several research focus on the extension of these models especially BPMNDF which aims to harmonize decision-making throughout a single business process. The current challenge is to extend the BPMNDF in order to cover business process in a distributed and cooperative environment. In this paper, we propose the Multi-Agent BPMN Decision Footprint (MABPMNDF) which is a novel model based on both BPMNDF and MAS to support decision-making in distributed business process.

Résumé

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

Résumé

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.

Résumé

In recent years, the Object Management Group (OMG)  has  focused  its  work  to  improve  the  business process modeling on multiple axes. The investigation in the domain  of  the  decision-making  has  resulted  in  its externalization through the invention of the Decision Model and Notation  (DMN). The latter, as presented  by OMG, is designed  as  a  supplement  to the  Business  Process  Model and  Notation  (BPMN),  to  model  decision-making  in business process.  DMN  covers  several  aspects  of  decision-making, but some factors are not explicitly mentioned, such as  harmonization,  synergy  and  uncertainty.  Since  the decision is based on modeling, serialization and integration of business  rules in the  business  process,  several questions arise  around  these problems.

In  this paper,  we  study the structure  of  business  rules  favoring  harmonization  of decisions  and  we  propose  an  additional  approach  for business  rules  serialization  through  NoSQL  databases, specifically MongoDB as a Document-Oriented database.

Résumé

Nowadays, one of the companies challenges is to benefit from their Business Intelligence (BI) projects and not to see huge investments ruined. To address problems related to the modelling of these projects and the management of their life-cycle, Enterprise Architecture (EA) Frameworks are considered as an attractive alternative to strengthen the Business-IT alignment. Business Process Model and Notation (BPMN) represents a pillar of these Frameworks to minimize the gap between the expectations of managers and delivered technical solutions. The importance of decision-making in business process has led the Object Management Group (OMG) to announce its new standard: Decision Model and Notation (DMN). In this paper, we propose the BPMN Decision Footprint (BPMNDF), which is a coupling of a BPMN with a novel DMN version. This enhancement has an additional component as a repository of all decisions along the process, used in order to ensure the harmony of decision-making.

Résumé

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.

Résumé

Since 1990, there has been a striking increase in using multi-agent systems to study renewable resources management systems. The ultimate objective is to contribute to decisions support on resources management. The adopted strategic decisions are always joined with access to resources norms. However, the defined norms are statics and suppose that all agents are not autonomous and always obey to the underlying norms which do not reflect reality. In previous work, we proposed ML-MA , a multi-level multi-agent architecture to support renewable resources management systems modeling. In this work, we focus on the integration of normative aspects in our architecture. Our approach is illustrated using “Ouled Chehida” case study from Tunisian pastoral context.

Résumé

No doubt, the flexible job shop problem (FJSP) has an important significance in both fields of production management and combinatorial optimization. For this reason, FJSP continues to attract the interests of researchers both in academia and industry. In this paper, we propose a new multi-agent model for FJSP. Our model is based on cooperation between genetic algorithm (GA) and tabu search (TS). We used GA operators as a diversification technique in order to enhance the searching ability of TS. The computational results confirm that our model MAS-GATS provides better solutions than other models.

Résumé

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.

Résumé

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.

Résumé

Analyzing human behaviors during emergency situations contributes to build efficient emergency management plans. Indeed, research shows that emotions have a major influence on human behavior particularly to respond to highly emotive events such as those happening in emergency situations. Therefore, it is recognized that they are necessary to produce human-like behaviors in artificial agents. In this paper, we present an emotional agent model of human civilians in an emergency context. The aim is to model and to simulate the emotion generation process and the impact of the elicited emotions on civilian behaviors in an emergency situation during a disaster.

Résumé

Agent based social simulations are becoming prevailing tools in the context of human behavior studies. Researchers in psychology, cognitive science and neuroscience have proved the prominent role of emotion on cognition and behavior. Particularly, during emergency situations, human emotional dynamics have a major effect on behavior. In this context, we aim to study the role of emotions in reproducing human-like emotional civilian agents. The objective of the current research work is to model and to simulate human emotional dynamics and their effect on the behaviors of civilians in emergencies. In this article, we describe an emotional agent model that integrates a computational model of emotions. Agent perceptions are subject to a cognitive appraisal process to generate agent emotions. These have an effect on the generation of agent behavior.

Résumé

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.

Résumé

Multi-agent systems are widely used in renewable and natural resources management. Multi-agent systems are able to manage the complexity of such systems characterized by a large number of interacting entities with different levels of granularity and including dynamics of different contexts (ecological, economic, social). In this work, we propose a generic multi-level architecture for renewable and natural resources management.

Résumé

The Flexible Job Shop problem (FJSP) is an important extension of the classical job shop scheduling problem, in that each operation can be processed by a set of resources and has a processing time depending on the resource used. The objective is to minimize the make span, i.e., the time needed to complete all the jobs. This works aims to propose a new promising approach using multi-agent systems in order to solve the FJSP. Our model combines a local optimization approach based on Tabu Search (TS) meta-heuristic and a global optimization approach based on genetic algorithm (GA).

Résumé

Multi-agent technology provides high level organizational concepts (groups, roles, commitments, interaction protocols) to structure, coordinate and ease the adaptation of distributed systems efficiently. This paper proposes to model a grid scheduling system as a multi-agent system organization. The resulting organizational model, based on the Agent Group Role meta-model of Ferber, is evaluated at the conceptual and implementation level. At the conceptual level, we evaluate the efficiency, robustness and flexibility of our model. At the implementation level, the analysis and the evaluation of our proposition, done through simulations, show its efficiency.

Résumé

Grid is known to be a heterogeneous, distributed and dynamic environment. In order to take fully advantages from grid power, Grid scheduling must take into consideration the environment’s constraints and be adaptive. In this work, Grid architecture is fully rethought in terms of agents in order to implement a cooperative and adaptive scheduling. At a macro level, our architecture enables flexible cooperation among its components using high level interaction protocols. At the micro level, agents in charge of scheduling perform an adaptive behaviour since they are able to perceive their environment and its disturbances, to reason and to deliberate about the actions to undertake in order to adapt. This is made possible by the use of Belief-Desire-Intention mechanisms. For that purpose, we propose a conceptual model useful for the perception function. Also, a typology of adaptive rules useful for the deliberation step is given. Component’s behaviour are specified and simulated with Petri-Nets

Résumé

Un Ordonnanceur de Grille (OG) a pour objectif d'optimiser l'utilisation des ressources mises à sa disposition. Le plus souvent, ce composant manque de flexibilité dans sa conception et a des difficultés à s'adapter aux diverses perturbations (fluctuation de la qualité de service, arrivée ou départ de nouvelles ressources, arrivée de travaux prioritaires, etc). L'objectif de cet article est de proposer une architecture orientée agents de type BDI (Belief Desire Intention) pour permettre à l'OG de s'adapter à ces perturbations et de travailler en coopération avec ses accointances. L'OG proposé fonctionne en boucle selon un schéma perception-délibération-action. La perception de l'environnement et de ses perturbations est rendue possible ici à l'aide d'un modèle conceptuel qui décrit à la fois la structure de la Grille et son fonctionnement. La délibération décide des actions à entreprendre (migration d'application, changement de plan d'ordonnancement, changement de politique d'attribution des tâches,..) pour s'adapter aux perturbations sur la base de règles qui proposent différents types d'adaptation selon les événements détectés. L'action correspond à la mise en oeuvre des décisions prises lors de la délibération.

Résumé

We consider a supply chain consisting of n locations replenished at the beginning of each period
by a supplier. These locations may coordinate in order to balance their inventory level through
transshipment. Transshipment is the items transfer from location having an inventory excess to
another in need. The transshipment problem consists to determine the initial inventory level
where a transshipment policy is practiced. In this work, we consider the transshipment problem
characterized by a non-negligible transshipment lead times and a limited transportation mean
capacity. Our aim is to find a transshipment policy that reduces the inventory costs and improve
the customer fill-rates. To realize this aim, we proposed a new formal transshipment model in
which the period is divided into a set of sub-periods and the transshipment decision is made at
the end of one of them. We also introduced a multi-agent model allowing to simulate the
cooperated behavior of the inventory locations.

Résumé

Learning agents have to deal with the exploration-exploitation
dilemma. The choice between exploration and exploitation is very difficult in
dynamic systems; in particular in large scale ones such as economic systems.
Recent research shows that there is neither an optimal nor a unique solution for
this problem. In this paper, we propose an adaptive approach based on meta-rules
to adapt the choice between exploration and exploitation. This new adaptive approach relies on the variations of the performance of the agents. To validate the
approach, we apply it to economic systems and compare it to two adaptive methods: one local and one global. Herein, we adapt these two methods, which were
originally proposed by Wilson, to economic systems. Moreover, we compare different exploration strategies and focus on their influence on the performance of
the agents

Résumé

Economic markets are complex systems. They are characterized by a large and dynamic population of firms. To deal with this complexity, we propose an adaptive multiagent system which models a set of firms in competition with each other within a shared market. The firms are represented by agents; each firm is represented by an adaptive agent. We show the advantages of adaptive agents to represent firms. Moreover, we underline the limits of the economic models which account for the firms only and ignore the organizational forms. We propose a new adaptive multiagent model that includes the organizational forms into the economic models. We simulate this model and discuss its advantages.

Résumé

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.

Résumé

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.