Dissertations / Theses on the topic 'Décision multi-agents'
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Boussard, Matthieu. "Planification multi-agents multi-objectifs : modèle et algorithme." Caen, 2008. http://www.theses.fr/2008CAEN2065.
Full textThis thesis deals with the coordination of a group of autonomous agents in the real world. So, we have to take into account uncertainty about action's outcome, about other agent's behavior and also the changes in the environment. We are using Markov decision processes (MDP), whose allow to manage those uncertainties in a decision process. In order to manage the interactions with the other agents, we give a formalism to express them, and also we give a solution to integrate them in a on-line decision process. This is an extension of the Markov Decision Processes where the agent are trying to optimize their own reward as well as the welfare of the group. This is a mutlicriteria decision problem, and we give it a solution. Once this formalism built, we tackle some classical coordination problems : platooning, spatial coverage, coalitions formation. Those applications allow us to apply with success the principle given at the beginning of the thesis. The extensions of this work will be dealing with on-line learning, and also game theory in order to detect and to solve deadlocks
Dafflon, Baudoin. "Modèle multi-agent d'inspiration physique pour la prise de décision : Application à la conduite en convoi." Thesis, Belfort-Montbéliard, 2014. http://www.theses.fr/2014BELF0240/document.
Full textBaudoin Dafflon’s doctoral work is placed in the general frame of self-organised systems. This kind of systems bases on the hypothesis that their organizationcan be the result of the individual behaviour of each one of the autonomous and proactive component entities. This emergent organization satisfies the objectives entrusted to the self-organizing system. This thesis is mainly directed to application domains in which the self-organizing system is composed of intelligent, frequently mobile material devices places in a physical, uncertain environment. Case-studies made included in this Thesis belong to the vehicle platoon problem.This Thesis interests mainlyto the decision-making problem of the self organizing systems of this kind. This aspect is particularly important when the system evolves in an uncertain environment. Uncertainty can be the consequence of an imperfect knowledge of the environment or because of the occurrence of unpredictable events. In those situations the autonomous entities have to decide locally about the best action to be performed in order for the global organization to be maintained. Even if information exchange among autonomous entities is not excluded a-priori, this doctoral work has been done under the restriction of non-communication, in order to investigate the reach of completely de-centralised approaches.Among the contributions of this thesis we can mention the following. Firstly, the proposal of an architecture that separates decision making and control, thereby allowing a simpler integration of uncertainty-management. An example from the application domain (vehicle platoons) is obstacle avoidance. Secondly, this thesis introduces a hierarchy of multi-agent systems such that decision-making is also conceived as a self-organized process in a virtual agent’s world. The later is built from an abstraction process based on the perceptions produced by material agents. Lastly, this thesis proposes physics-inspired interaction mechanisms for virtual agents. Those interaction models based on phenomena such as attraction-repulsion forces or gas dynamics, allow for a computational decision making process based on the laws and properties of the adopted physical models.Doctoral work presented in this Thesis has been done in the framework of the ANR-VTT project
Delecroix, Fabien. "Dialoguer pour décider : recommandation experte proactive et prise de décision multi-agents équitable." Thesis, Lille 1, 2015. http://www.theses.fr/2015LIL10011/document.
Full textIf decision making can be a pure individual process, it can involve several actors and present social aspects. In this thesis, I consider two types of social decision process : supported decision making and collective decision making. Concerning supported decision making, two actors have distinct roles : the decision maker and the assistant. Here, the decision maker is a human agent and the assistant a software one. In many applications, the dialogical abilities of the assistant are deceptive and the dialogue lacks of consistency. To tackle this problem, we design a proactive dialogical agent aiming for the credibility in conversation and the relevance of recommandations : our agent leads the conversation in asking relevant questions to collect the preferences of the decision maker and use them in recommending the alternatives that fit the most. We apply our approach on the e-commerce field. The second contribution concerns collective decision. The objective is to define a process that lead to a fair agreement, even if participants have incomplete preferences. For this purpose, I define the fair agreements by applying the leximax criterion on the rank of alternatives. Then, I propose a negotiation protocol to reach such agreements and the strategy is taken into account to evaluate it. Finally, the protocol is applied to the search of a meeting point in a maze
Cointe, Nicolas. "Jugement éthique pour la décision et la coopération dans les systèmes multi-agents." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSEM043/document.
Full textThe increasing use of multiagent systems in various fields raises the need of autonomous agents able to take into account such ethical principles in their decisions. More and more propositions are published, but they are often agent-centered and they don’t consider the issues raised by the interactions between artificial agents and possibly humans, potentially using another ethics. Our goal is to give the agents the ability to reason on ethics to enable an ethics-based cooperation in multiagent systems. This work presents a model of ethical judgment for artificial autonomous agents in multiagent systems both useful to influence their decisions and behaviors, and describes an ethics-based cooperation framework. This model distinguishes the morality (or theory of the good), describing the goodness of actions in a context regarding a set of moral values and moral rules, and ethics (or theory of the right), describing the rightness of an action regarding a set of ethical principles. The use of this model in the decision process generates a conform behavior regarding the chosen theories of good and right. An agent may also use this model to judge the observed behavior of the other agents and employ this judgment to adapt its own behavior towards the judged agents. The detailed presentation of this model is followed by some experimentations to show the use of this model in a realistic application based on an ethical asset management scenario. The results show how the behaviors of the agents might be impacted and the efficiency of this model to discriminate the behaviors of the others
Shen, Ying. "Élaboration d'ontologies médicales pour une approche multi-agents d'aide à la décision clinique." Thesis, Paris 10, 2015. http://www.theses.fr/2015PA100040/document.
Full textThe combination of semantic processing of knowledge and modelling steps of reasoning employed in the clinical field offers exciting and necessary opportunities to develop ontologies relevant to the practice of medicine. In this context, multiple medical databases such as MEDLINE, PubMed are valuable tools but not sufficient because they cannot acquire the usable knowledge easily in a clinical approach. Indeed, abundance of inappropriate quotations constitutes the noise and requires a tedious sort incompatible with the practice of medicine.In an iterative process, the objective is to build an approach as automated as possible, the reusable medical knowledge bases is founded on an ontology of the concerned fields. In this thesis, the author will develop a series of tools for knowledge acquisition combining the linguistic analysis operators and clinical modelling based on the implemented knowledge typology and an implementation of different forms of employed reasoning. Knowledge is not limited to the information from data, but also and especially on the cognitive operators of reasoning for making them operational in the context relevant to the practitioner.A multi-agent system enables the integration and cooperation of the various modules used in the development of a medical ontology.The data sources are from medical databases such as MEDLINE, the citations retrieved by PubMed, and the concepts and vocabulary from the Unified Medical Language System (UMLS).Regarding the scope of produced knowledge bases, the research concerns the entire clinical process: diagnosis, prognosis, treatment, and therapeutic monitoring of various diseases in a given medical field.It is essential to identify the different approaches and the works already done.Different paradigms will be explored: 1) Evidence Based Medicine. An index can be defined as a sign related to its mode of implementation; 2) Case-based reasoning, which based on the analogy of clinical situations already encountered; 3) The different semantic approaches which are used to implement ontologies.On the whole, we worked on logical aspects related to cognitive operators of used reasoning, and we organized the cooperation and integration of exploited knowledge during the various stages of the clinical process (diagnosis, prognosis, treatment, therapeutic monitoring). This integration is based on a SMAAD: multi-agent system for decision support
Benabbou, Nawal. "Procédures de décision par élicitation incrémentale de préférences en optimisation multicritère, multi-agents et dans l'incertain." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066101/document.
Full textThis thesis work falls within the area of algorithmic decision theory which is at the junction of decision theory, operations research and artificial intelligence. Our aim is to produce algorithms allowing the fast resolution of decision problems in complex environments (multiple criteria, multi-agents, uncertainty). This work focuses on decision-theoretic elicitation and uses preferences to efficiently determine the best solutions among a set of alternatives explicitly or implicitly defined (combinatorial optimization). For combinatorial optimization problems, we propose and study a new approach consisting in interleaving incremental preference elicitation and preference-based search. The idea is to use the exploration to identify informative preference queries while exploiting answers to better focus the search on the preferred solutions. This approach leads us to propose incremental elicitation procedures for multi-objective state-space search problems, multicriteria shortest path problems, multicriteria minimum spanning tree problems, multi-agents knapsack problems and sequential decision problems under uncertainty. We provide theoretical guarantees on the correctness of the proposed algorithms and we present numerical tests showing their practical efficiency
Benabbou, Nawal. "Procédures de décision par élicitation incrémentale de préférences en optimisation multicritère, multi-agents et dans l'incertain." Electronic Thesis or Diss., Paris 6, 2017. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2017PA066101.pdf.
Full textThis thesis work falls within the area of algorithmic decision theory which is at the junction of decision theory, operations research and artificial intelligence. Our aim is to produce algorithms allowing the fast resolution of decision problems in complex environments (multiple criteria, multi-agents, uncertainty). This work focuses on decision-theoretic elicitation and uses preferences to efficiently determine the best solutions among a set of alternatives explicitly or implicitly defined (combinatorial optimization). For combinatorial optimization problems, we propose and study a new approach consisting in interleaving incremental preference elicitation and preference-based search. The idea is to use the exploration to identify informative preference queries while exploiting answers to better focus the search on the preferred solutions. This approach leads us to propose incremental elicitation procedures for multi-objective state-space search problems, multicriteria shortest path problems, multicriteria minimum spanning tree problems, multi-agents knapsack problems and sequential decision problems under uncertainty. We provide theoretical guarantees on the correctness of the proposed algorithms and we present numerical tests showing their practical efficiency
Diago, Ndeye Arame. "Mécanismes de négociation multilatérale pour la prise de décision collective." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSE1174/document.
Full textCollective decision making is a process in which many participants with different interests interact in order to build a solution to their problem. It is inherent to many organisations and companies. Nowadays, the advances in Artificial Intelligence, notably, Multi-Agents Systems enabled the automation of decision-making processes in order to analyse and to better understand how these mechanisms work. A collective decision may be made by using a voting system or by using negotiation. In this thesis, we focus on multilateral negotiation for collective decision making by proposing negotiation models. The proposed models based on heuristic approach. The agents interact with them in order to build a solution to their problem. This context is different from models based on game theory where the set of possible solutions are supposed to be known by all agents. So heuristic negotiation issue is that agents' reasoning may be very complex. This complexity grows where the number of agents and issues to be negotiated are important. The goal of this research work consists of devising negotiation mechanisms where agents'interaction are fully decentralized. We focus on organisation aspect of the multi-agent system by using divide and conquer approach in order to reduce the negotiation complexity and hence to facilitate research of agreements. Our works tackle negotiation under different contexts which lead us to bring three contributions which focus on agents' organization, interaction protocols, negotiation object, concession strategies and effective and fair solution concept. The proposed mechanisms are implemented in JavaJade. We analyse the convergence of the negotiation, negotiation time and quality of the solution. Our models are compared with a centralized approach where all of the agents are gathered around one group to negotiate. Our empirical analyses show that our propositions allow the agents to reach collectives agreements
Morge, Maxime. "Syst'eme dialectique multi-agents pour l'aide 'a la concertation." Phd thesis, Ecole Nationale Supérieure des Mines de Saint-Etienne, 2005. http://tel.archives-ouvertes.fr/tel-00797376.
Full textFerrand, Nils. "Modèles Multi-Agents pour l'Aide à la Décision et la Négociation en Aménagement du Territoire." Phd thesis, Université Joseph Fourier (Grenoble), 1997. http://tel.archives-ouvertes.fr/tel-00003562.
Full textKabachi, Nadia. "Modélisation et Apprentissage de la Prise de Décision dans les Organisations Productives: Approche Multi-Agents." Phd thesis, Ecole Nationale Supérieure des Mines de Saint-Etienne, 1999. http://tel.archives-ouvertes.fr/tel-00822831.
Full textFerrand, Nils. "Modèles multi-agents pour l'aide à la décision et la négociation en aménagement du territoire." Grenoble 1, 1997. http://www.theses.fr/1997GRE10113.
Full textGamoura, Samia. "Modélisation et simulation des processus collaboratifs dans les chaînes logistiques : une approche multi agents." Lyon 2, 2007. http://theses.univ-lyon2.fr/documents/lyon2/2007/chehbi_s.
Full textThis thesis is related to decision making and collaboration within a supply chain context. After a critical review on supply chain activities and their management, we focuse on the decision making complexity and collaboration forms related to manufacturing supply chains. This study proposes a model "MASC" based on cognitive and autonomous agents. MASC model is generic and aims at modeling any supply chain structure. It contributes to facilitate the collaborative management between activities. This model can be viewed as a mono and multi criteria decision making tool. It can also be considered as a strategic analysis tool for supplier managers in order to understand the dynamic and uncertainty of the entreprise environment. The usefulness of MASC is illustrated on an academic context within the regional project COPILOTES (Rhône-Alpes region), and then it has been validated on an industrial case study (pharmaceutical and parapharmaceutical entreprise (LAAP))
Ouzizi, Latifa. "Planification de la production par co-décision et négociation de l'entreprise virtuelle." Metz, 2005. http://docnum.univ-lorraine.fr/public/UPV-M/Theses/2005/Ouzizi.Latifa.SMZ0501.pdf.
Full textProduction planning using co-decision and negotiation whitin a virtual enterprise in this thesis, we are interested to a problem related to the evolution of the industrial production which is organized innetworks of enterprises coordinating their activities to produce the same finished product. After a detailed bibliographical study on modelling, coordination and planning within supply chains in general and on thevittual enterprise (VE) in particular, we centred our research task on collaborated and coordinated production's modellingand planning of a virtual enterprise. Our work consists in proposing on the one hand an architecture of the virtual enterprise by level and, on the other hand, models of planning which make it possible to ensure a plan of feasible and quasi optimal production planning according to the architecture suggested. This is carried out initially by coordinating enterprise's plannings of the same level, then by coordinating plannings of each level with those of upstream and downstream levels. To achieve our goal, we proposed a whole of definitions of data which we used and which we consider necessary for a quasi complete modelling of planning processes within the virtual enterprise. The definition of forecasts and contracts with outside make it possible to know the extemal environment of the VE. In the same way, definitions of ceulated curves, contracts and models of cost used by the partners make it possible to know the internal environment with the VE as well as the retained objectives for a virtual enterprise. To describe a global planning process of the VE in a progressive way, we start with the description of a node of the VE by specifying its various planning problems and proposing optimization models to minimize the production costs. Then, we studied problems of planning on a level by describing and modelling coordination between nodes of the same level. At the end, we describe the iterative process of supply chain planning. In order to assure coordination within the virtual enterprise, we use negotiation and mediation. Negotiation permits to partners to wide the field of planning. While mediation permits, using constraints relaxation, to solve conflicts in the event of no convergence of negotiations. Highlight distributed and centralized models of planning, we used the multi-agents approach. After a description of the different agents constiiuting our architecture and their tûnctionalities, we describe the various behaviours, data and messages used by the agents to ensure communications between them
Fayech, Besma. "Régulation des réseaux de transport multimodal : systèmes multi-agents et algorithmes évolutionnistes." Lille 1, 2003. https://pepite-depot.univ-lille.fr/LIBRE/Th_Num/2003/50376-2003-323.pdf.
Full textHamel, Athmane. "Conception participative et coopérative de simulations multi-agents : application à la filière avicole." Paris 9, 2006. https://portail.bu.dauphine.fr/fileviewer/index.php?doc=2006PA090071.
Full textIn order to simulate the impacts of individual behaviours on organisations’ objectives, participatory approaches are well-established methods. This thesis proposes a new Approach for Cooperative Knowledge Acquisition (Acka). Acka is a cooperative method, based on the experts’ participation within role-playing games during meetings. Our approach proposes to build a metaphoric model as a domain model which is then used to design the multi-agent simulation model. The application of Acka to study microscopic decision-making processes within the poultry production system, and to design a multi-agent participatory simulation is illustrated. This simulation model, called AviSim, aims at understanding the impacts of individual decisional behaviours on the use of raw materials within poultry. Acka&AviSim proposes a new participatory approach, based on the coupling of two kinds of representation modes: observation-based mode and cognition-based mode. Finally, a personal reflection about the participatory design is proposed
Tchikou, Mahmoud. "Un environnement de conception multi-agents pour le pilotage des systèmes de production." Informatique, 2004. http://www.theses.fr/2004PAUU3011.
Full textFace to strong competitive markets, current companies tend to new methods of production, from a logic of "planning" type of production to a logic of "Just in time " type. In this context, the system which allows to control the production has to be a modular, flexible and reactive system. The hierarchized classical approaches don't permit any more to take into account the complexity linked to such system. That's why, we propose an approach which has a reactive, distributive, and emergent properties to control the system of production, based on multi-agent system principles. The aim of this thesis is to propose an approach and model in order to facilitate the design of modern production activity control. We have proposed a model based on organisational concepts such as the groups and roles, concepts of interaction of the FIPA (intelligent Foundation for physical agents) such as the protocols
Martelloni, Paul-Henri. "Modélisation et Simulation des systèmes complexes spatialisés. Utilisation de Systèmes Multi-Agents et Multi-composant pour la gestion des pêcheries." Thesis, Corte, 2021. http://www.theses.fr/2021CORT0016.
Full textThe computer science research team at our university works in modelling and simulation to studycomplex natural systems in a holistic way.In this work, we have set ourselves the goal of using computer simulation as a virtual laboratory todesign a decision support tool in a multidisciplinary context.The focus of our work is to propose a generic executable model to allow decision support and to useit towards the modelling of a fishery system. We propose to apply our work to the management offish stocks in Corsica.This led us to the following approach: the first step is the representation of the complex system.For this we have looked for a paradigm to represent components within a hierarchical structurecapable of interactions and autonomous decision making.The agent paradigm lends itself very well to the representation of complex bio-economic systems.Then, the question of the robustness of the approach arose. For this purpose, we used the theory ofmodeling and simulation (TM\&S) proposed by B.P. Zeigler. In our case, the PDEVS formalism canbe considered as a unifying and pivotal formalism. It allows the inclusion of other concepts, we speakof multi-modeling.We complement it with the agent paradigm in order to benefit from itsexpressiveness and its ability to describe entities (the agents) simply, their mutual interactions, andthe environment in which they evolve. Finally, in order to respect a formal framework, essential to thepreliminary work of conceptualization, we use the DPDEMAS formalization proposed by R.Franceschini and already developed in our team. This formalization offers in its original form aninteresting analogy between a Multi-Agent System (MAS) and the PDEVS and DSDE models(dynamic version of PDEVS). We find a description of the agent from a body which models itsphysical representation in an environment, as well as from a mind which is the place of decisionmaking.This led us to consider the problem of decision making. The central issue was therefore to proposean executable model that is sufficiently generic to allow decision support and to use it in the case ofmodeling a fishery. To do so, we propose an approach that provides agents with bricks inspired bySoar. An optimization brick allowing to refine the agents' decisions. A reinforcement learning brickallowing agents to develop their knowledge in a given situation.We complete this description with a first didactic example before applying our approach to twoexamples of modeling a fishery system based on 50 years of data.The first example is a 5-component model to simulate scenarios with quotas.The second example is a 6-component model to simulate scenarios with quotas, and additionallytaking into account space and migrations between areas. Nevertheless, these two models only aimat validating our approach. Indeed, if thanks to these two examples, we obtain coherent resultsallowing us to validate their behaviour, these models are purely theoretical and do not represent thereality of the system sufficiently well to be used to assist in the management of fishery resources.The perspectives that we envisage in the future are on the one hand the integration of new learningand decision methods, to develop a fishery model more representative of the reality or to use ourapproach to treat other case studies
Brigui-Chtioui, Imène. "Une approche multi-agents pour les enchères multicritères à points de référence dans le commerce électronique." Paris 9, 2006. https://portail.bu.dauphine.fr/fileviewer/index.php?doc=2006PA090050.
Full textThis thesis deals with multicriteria auctions in electronic commerce. Our research aims to design an auction system that addresses the shortcomings of the existing works. We propose a multicriteria auction system based on reference points that makes easier the preference expression and insures an auction convergence toward the buyer preferences as well as a control on each attribute of the item and a non compensatory aggregation logic. In our work, we combined two disciplines Decision Aid and Multiagent Systems. Decision aid theory allowed us to define the system key components : a preference model, an aggregation model and a counterproposal mechanism. Multiagent systems are particularly adapted to our issue thanks to the autonomous, personalized and rational character of the agents. These characteristics allow agents to represent faithfully human actors on the web and to act on their behalf. In this thesis, we highlight the properties of the proposed multicriteria auctions and we propose an experimental validation of our system
Boissin, Denis Sébastien Emile. "Formalisation de l'apport des organisations-frontières dans la prise de décision publique par le biais d'un modèle multi-agents." Nice, 2011. http://www.theses.fr/2011NICE0038.
Full textAs the faith in Science long guided the development of society, it is now questioned by the consequences of technologies that arose during the last century. Our society must now face complex interdependent issues, with large time and space scales of biogeochemical and social consequences, of which science is both a cause and a solution. As the natural behavior of private agents does not allow for solving naturally those issues, it is necessary to call for a third-party regulator in order to maximize the well-being of society on both environmental and economic dimensions. The complexity and uncertainty are internal characteristics of environmental issues that prevent the possibility of obtaining an exact information regarding the possible states of the world and the probability of their occurrence. Therefore, the public decision aiming at sustainably enhancing the state of the environment by acting on the behavior of the various agents involved, can be considered as making choices with irreversible consequences on the well-being of society, and especially that of future generations, on the basis of an information that is not sufficient, not complete and not perfect. As the decision-maker is not able to grasp the technicality and specificity involved, he relies on experts to be able to decide knowingly. Under uncertainty, the decision-making process requires a projective approach based on available knowledge that only persons holding a deep knowledge and experience can provide. But this expertise can not be considered an exogenous factor, as the possible states of the world and their probability of occurrence identified is an information constructed under influences from both experts and decision-makers. .
Klein, François. "Contrôle d'un Système Multi-Agents Réactif par Modélisation et Apprentissage de sa Dynamique Globale." Phd thesis, Université Nancy II, 2009. http://tel.archives-ouvertes.fr/tel-00432354.
Full textMorvan, Gildas. "Approche multi-agents d'un système d'aide à la décision en environnement dynamique et incertain. Application à l'entomologie médico-légale." Thesis, Artois, 2009. http://www.theses.fr/2009ARTO0204/document.
Full textThe work presented in this thesis deals with modelling and decision support issues in the context of complex systems. Specifically, we investigate the coupling of agent-based simulations and inverse problem resolution methods. Thus, a generic architecture of decision support system is proposed. We identify two problems related to the implementation of this architecture: the validation of simulation parameters and the observation of agent-based simulations. We offer some answers to solve them. The notion of inverse problem is redefined in the context of decision support in a multi-model framework. Therefore, a resolution method and heuristics, based on ideas from works on abductive reasoning, are proposed. This work is then applied to the conception of a decision support system dedicated to forensic entomology. This research area, midway between forensic sciences and entomology, aims to develop post-mortem estimation methods based on entomological indices, i.e., insects (mainly necrophagous diptera) or insect remains, sampled on or around the cadaver. In the context of this work, done in collaboration with forensic entomology laboratory of the Legal Medicine Institute of Lille, we present: • an agent-based model of necrophagous diptera in a complex environment such as a dead body in a specific ecosystem, taking into account more parameters than conventional methods, • an implementation of the decision support system architecture mentioned above, based on this model
Ben, othmane Amel. "CARS-Un système multi-agent pour la prise de décision dans des applications spatiotemporelles incertaines." Thesis, Université Côte d'Azur (ComUE), 2017. http://www.theses.fr/2017AZUR4086/document.
Full textRecently, many real-world applications where different entities interact in a dynamic environment, consider the use of agents in their architectures due principally to their autonomy, reactivity and decision-making abilities. Though these systems can be made intelligent, using Artificial Intelligence (AI) techniques, agents still lack of social abilities and have limited knowledge of their environment and in particular when it comes to a dynamic environment. In fact, when operating in the real world, agents need to deal with unexpected events considering both changes in time and space. Moreover, agents must face the uncertainty, which pervades real-world scenarios in order to provide an accurate representation of the world. In this thesis, we introduce and evaluate a formal framework for recommending plans to agents in the decision making process, when they deal with uncertain spatio-temporal information. The agent-based architecture we propose to address this issue, called CARS (Cognitive Agent-based Recommender System), has been designed by extending the well-known Belief-Desire-Intention (BDI) architecture to incorporate further capabilities to support reasoning with different types of contextual information, including the social context. Uncertainty on the agent's beliefs, desires and intentions is modeled using possibility theory. To meet the requirements of real-world applications, e.g., traffic and navigation recommendation systems, we define a spatio-temporal representation of the agents' beliefs and intentions. Using such a formal framework, anticipatory reasoning about intentional dynamics can be performed with the aim to recommend an optimal plan to a certain user. Since spatio-temporal data is often considered as incomplete and/or vague, we extended the formal framework with a fuzzy representation of spatio-temporal beliefs and intentions. The framework is evaluated through an Agent Based Simulation (ABS) in a real-world traffic scenario. This ABS allowed us to create a virtual environment to test the impact of the different features of our framework as well as to evaluating the main strengths and weaknesses of the proposed agent architecture
Ferraris, Christine. "Acquisition des connaissances et raisonnement dans un univers multi-agents : application à la prise de décision en génie civil urbain." Nancy 1, 1992. http://docnum.univ-lorraine.fr/public/SCD_T_1992_0024_FERRARIS.pdf.
Full textZeddini, Besma. "Modèles d'auto-organisation multi-agents pour le problème de transport à la demande." Le Havre, 2009. http://www.theses.fr/2009LEHA0025.
Full textThis PhD thesis is motivated by the proposal of multiagent models for the Dial A Ride Problem with Time Windows (DARPTW). The DARPTW is a highly complex dynamic problem, for which a multiagent design is relevent. Our proposals focus on Self-Organization models in multiagent systems that allows for the consideration of new criteria for the assessment of the proposed systems, which with the strict consideration of the utility of the transport operator. In our work, we propose several multiagent architectures for the implementation of the DARPTW system. After experimentally evaluating the different architectures, we popose algorrithmic improvements of the best architecture. The objective of these improvements is to palliate the drawbacks related to the myopic behavior of insertion heuristics and the sequentiality of their insertion process. On the one side, we relax the constraint on the non-revokation of assignment decisions by allowing vehicles to exchange customers that they have inserted. On the other side, by adopting an extension of the Contract Net Protocol, we propose to Vehicle agents to process several customers in parallel. The third contribution of this PhD thesis is the proposal of two Self-Organization models (spatial and temporal) allowing a better spatial and temporal coverage of the network. A set of experiments validate our proposals. Finally, we implement a platform allowing for the deployment of DARPTW systems
Ouzrout, Yacine. "Architectures collaboratives pour l'aide à la décision dans les entreprises en réseau." Habilitation à diriger des recherches, Université Lumière - Lyon II, 2012. http://tel.archives-ouvertes.fr/tel-00793994.
Full textNdiaye, Mamadou. "Analyse vectorielle des signaux intracérébraux pour la compréhension des mécanismes d'initation et de propagation des crises d'épilepsies : approche comportementale par système multi-agents." Rennes 1, 2007. http://www.theses.fr/2007REN1S090.
Full textThis work is focused on the study of cooperative agent's approaches in analysis and interpretation of epileptic signals, based on intracerebral EEG signals analysis. It studies the dynamics of neuronal networks in the partial temporal lobe epilepsy. A descriptive, quantitative and global method of organization analysis of the critical paroxystic events is proposed and applied to all the vectorial signals recorded during the pre-surgical investigation. Our approach associated signal processing in multi-agent system. Every epileptic signal is associated with a cooperative agent asked to characterize its individual properties and its links with the other agents. This transposition to electrophysiological space (signals) in an agent space (multi-agent platform) allowed to organize, to control the various computations, to assure their coordination by integrating into best specificities of each and to bring to the foreground all the interesting combinations between cerebral regions
Le, Pors Thierry. "Simulation cognitive de la prise de décision d'experts ; application au trafic maritime." Phd thesis, Université de Bretagne Sud, 2010. http://tel.archives-ouvertes.fr/tel-00547128.
Full textBasileu, Cynthia. "Modélisation structurelle des réseaux sociaux : application à un système d’aide à la décision en cas de crise sanitaire." Thesis, Lyon 1, 2011. http://www.theses.fr/2011LYO10240/document.
Full textTo manage a public health crisis resulting from an outbreak of a large-scale pandemic, it is necessary to be capable of taking adequate measures very quickly. These measures must be taken to protect the productive capacity of the economy. Consequently, I have focused on the development of a « decision-making support » model with hybrid agents simulating the spreading of a pandemic, which is established on the medical characteristics of the virus as well as the socioeconomic structure of the concerned geographical zone. This socioeconomic structure being at the centre of the model, a pretopological modelling of the concept of social network is therefore proposed and integrated into the approach agent
Ali, Ahmad. "L' approche multi-agents pour le pilotage des systèmes complexes appliquée aux systèmes du trafic urbain." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2009. http://tel.archives-ouvertes.fr/tel-00725327.
Full textNdiaye, Soulemane. "Une approche multi-agents pour l'aide aux processus decisionnels complexes : une application a l'intelligence economique." Toulouse 1, 1997. http://www.theses.fr/1997TOU10079.
Full textThis thesis deals with complex decision making. First, different approaches dealing with decision making are investigated. Based upon that, a cognitive approach of decision is introduced and a model of complex decision making is proposed. This model is related to cognitive planning mechanisms (schema, anticipation), and construction and manipulation of models (operative models). In a second time, decision support and decision support systems are analysed. Systems and techniques related to complex decisions support are discussed. Complex decision support, in the perspective of augmenting managers' capacity, underlines the construction and manipulation of operative models. An agent oriented meta-model is proposed to support both activities. Lastly, simeco, a toolkit fully integrating this meta-model is presented. Simeco allows to create and modify applications implementing operative models. An application dedicated to economic intelligence is then described
Basileu, Cynthia. "Modélisation structurelle des réseaux sociaux : application à un système d'aide à la décision en cas de crise sanitaire." Phd thesis, Université Claude Bernard - Lyon I, 2011. http://tel.archives-ouvertes.fr/tel-00755031.
Full textAgbossou, Igor. "Modélisation et simulation multi-agents de la dynamique urbaine : application à la mobilité résidentielle." Phd thesis, Université de Franche-Comté, 2007. http://tel.archives-ouvertes.fr/tel-00924741.
Full textBuffet, Olivier. "Une double approche modulaire de l'apprentissage par renforcement pour des agents intelligents adaptatifs." Phd thesis, Université Henri Poincaré - Nancy I, 2003. http://tel.archives-ouvertes.fr/tel-00509349.
Full textZouhair, Abdelhamid. "Raisonnement à partir de cas dynamique multi-agents : application à un système de tuteur intelligent." Thesis, Le Havre, 2014. http://www.theses.fr/2014LEHA0009/document.
Full textAOur thesis works are related in the field of Decision Support System (DSS) for dynamic situations based on past experiences. Several approaches have been used in this area such as neural networks, Petri Nets and Hidden Markov Model but they suffer from some limitations in automated real-time management dynamic parameters. We propose a multi-agent multi-layer architecture based on Incremental Dynamic Case-Based Reasoning (IDCBR) able to study dynamic situations (recognition, prediction, and learning situations). We propose a generic approach able to learn automatically from their experiences in order to acquire the knowledge automatically. In addition, the static CBR systems suffer from some limitations such as the problem of the static management for dynamic parameters of the situation and they are unable to detect automatically the changes in its parameters in order to adapt the situation during their evolution. Based on the Case-Based Reasoning and multi-agent paradigm, we propose a modification of the static CBR cycle in order to introduce a dynamic process of Case-Based Reasoning based on a dynamic similarity measure able to evaluate in real time the similarity between a dynamic situation in current progress (target case) and past experiences stored in the memory (sources case) in order to predict the target case in the future. We validate the approach proposed by the implementation of an intelligent tutoring system prototype. In our approach Incremental Dynamic Case-Based Reasoning-Multi-Agent System (IDCBR-MAS), the past experiences are structured and modeled as traces. They include the interaction of the learner with the platform, which include history, chronology of interactions and productions left by the learner during his/her learning process. IDCBR-MAS designed and modeled with AUML language. Its agents have been implemented with JAVA and SMA / JADE platform
Zelfani, Margheni. "Ingénierie de la connaissance et raisonnement dans un univers multi-agents : Xpent-Cassis, un système à base de connaissances en géotechnique." Saint-Etienne, 1993. http://www.theses.fr/1993STET4031.
Full textKontarinis, Dionysios. "Debate in a multi-agent system : multiparty argumentation protocols." Thesis, Paris 5, 2014. http://www.theses.fr/2014PA05S025/document.
Full textIn this thesis multi-agent argumentation debates are studied. Our work is motivated by the issues which are raised when a large number of users interact and debate on the Web, by exchanging arguments on various topics. These issues are raised on the levels of representing the debating users' knowledge, representing the debate, computing the debate's conclusions, evaluating the debate's quality, defining specific protocols for user interaction, and studying debate strategies which users employ in order to achieve particular goals. This thesis' contribution consists in: a) proposing a way to model a multi-agent argumentation debate where the participants have different types of expertise, and proposing a way to aggregate their opinions; b) offering support to the agent who is arbitrating a debate, proposing a way to evaluate the quality of a debate on the basis of how confident we can be on its conclusions, and proposing solutions for improving the quality of a debate which lacks definite conclusions; c) offering support to the debating agents in order to determine which arguments they should put forward, studying dynamic argumentation systems, studying the potential ways in which an agent can influence a dynamic argumentation system in order to achieve his goal, studying the minimal change allowing an agent to achieve his goal, studying several argumentation strategies based on minimal change; d) defining, studying and evaluating multi-agent argumentation protocols, defining protocols of different types (1) based on numerical argument evaluation and (2) based on argument extensions, using different techniques to ensure a debate's coherence while ensuring some liberty of expression to the agents, and finally performing an important number of experiments (on debates) in order to test various strategies and evaluate them with respect to specific criteria
Apete, Geoffroy Kokou. "Optimisation médico-économique et organisation des services d'urgences hospitalières : apport des systèmes multi-agents." Phd thesis, Université du Droit et de la Santé - Lille II, 2011. http://tel.archives-ouvertes.fr/tel-00668083.
Full textMaurel-Entzmann, Françoise. "Capitalisation d'un savoir-faire industriel pour la réalisation d'un système d'aide à la décision à base de multi-agents : application dans une chaîne agro-alimentaire d'une malterie : projet C.O.R.M.O.R.A.N." Nancy 1, 1996. http://www.theses.fr/1996NAN10205.
Full textThe malting process is difficult to modelize because ofthe insufficient understanding of the interactions between the various process parameters. The purpose of the thesis is the achievement of quality and process control through a modelization of the know-how. The first part was dedicated to the choice of a knowledge-base tool in the different techniques of knowledge modelization. The implementation of this tool has allowed to formalize the expertise in the form of actions recommendations. For this purpose, several modelization techniques have been used, and they are described in this paper. The result of the know-how modelization in the malting process is a series of action recommendations which are later on validated through the industrial production data. This phase of validation is supported by the learning ability of the neuroagent. Moreover, the analysis of this validation, enrichies the expertise. These three modes constitute the basic elements of the global system of assistance to the decision making C. O. R. M. O. R. A. N. This system is presently operationnel and in use on one of the production sites
Veremme, Alexandre. "Intérêts et usages de la théorie des fonctions de croyance pour les systèmes d'aide à la décision basés sur les systèmes multi-agents. : application à l'entomologie médico-légale." Thesis, Artois, 2010. http://www.theses.fr/2010ARTO0205/document.
Full textThis work is based on the agent simulations (ABS), the cellular automata based simulations (CABS) and the theory of belief functions. The purposes consist in proposing solutions to complex problems and developping a general architecture for decision support system (DSS) organized around these three tools. Because this system resorts to the theory of belief functions (also called the evidence theory), we called it EDSS, i.e., evidential decision support system. The EDSS tries to explain an observation made on a complex real system. It uses:- ABS and CABS to simulate the complex system of study;- the belief function theory to represent and manipulate information within and around the simulations.The architecture is validated through a decision support system, named ForenSeek, dedicated to experts in forensic entomology. Forensic entomology is a method for estimating the time of death from determining the ages and species of insects collected on a cadaver. This technique faces with a set of complex phenomena, not easily discernible by the experts and having an impact on their final decisions. The EDSS ForenSeek uses the ABS and CABS to simulate the corpse decomposition. It incorporates a large number of ecosystem parameters and tests a large quantity of biological models. The theory of belief functions is central to this information fusion system. First results from real forensic expert's reports are presented
Kaddoussi, Aida. "Optimisation des flux logistiques : vers une gestion avancée de la situation de crise." Phd thesis, Ecole Centrale de Lille, 2012. http://tel.archives-ouvertes.fr/tel-00801728.
Full textTena-Chollet, Florian. "Elaboration d'un environnement semi-virtuel de formation à la gestion stratégique de crise, basé sur la simulation multi-agents." Phd thesis, Ecole Nationale Supérieure des Mines de Saint-Etienne, 2012. http://tel.archives-ouvertes.fr/tel-00741941.
Full textKontarinis, Dionysios. "Debate in a multi-agent system : multiparty argumentation protocols." Electronic Thesis or Diss., Paris 5, 2014. http://www.theses.fr/2014PA05S025.
Full textIn this thesis multi-agent argumentation debates are studied. Our work is motivated by the issues which are raised when a large number of users interact and debate on the Web, by exchanging arguments on various topics. These issues are raised on the levels of representing the debating users' knowledge, representing the debate, computing the debate's conclusions, evaluating the debate's quality, defining specific protocols for user interaction, and studying debate strategies which users employ in order to achieve particular goals. This thesis' contribution consists in: a) proposing a way to model a multi-agent argumentation debate where the participants have different types of expertise, and proposing a way to aggregate their opinions; b) offering support to the agent who is arbitrating a debate, proposing a way to evaluate the quality of a debate on the basis of how confident we can be on its conclusions, and proposing solutions for improving the quality of a debate which lacks definite conclusions; c) offering support to the debating agents in order to determine which arguments they should put forward, studying dynamic argumentation systems, studying the potential ways in which an agent can influence a dynamic argumentation system in order to achieve his goal, studying the minimal change allowing an agent to achieve his goal, studying several argumentation strategies based on minimal change; d) defining, studying and evaluating multi-agent argumentation protocols, defining protocols of different types (1) based on numerical argument evaluation and (2) based on argument extensions, using different techniques to ensure a debate's coherence while ensuring some liberty of expression to the agents, and finally performing an important number of experiments (on debates) in order to test various strategies and evaluate them with respect to specific criteria
Hanon, David. "Modèle décisionnel orienté comportement fondé sur le vote : Application à la navigation d'agents autonomes en environnement simulé." Phd thesis, Université de Valenciennes et du Hainaut-Cambresis, 2006. http://tel.archives-ouvertes.fr/tel-00135931.
Full textHamdani, Fatima Ezzahra. "Une approche d'aide à la décision de la prise en charge des personnes âgées." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSES059.
Full textIn France, elderly care is primarily intended for people aged 65 and over. It consists of hospital care (intra-hospital), and elder home care (extra-hospital) for patient in the territory closest to his / her own home. It organizes through the interweaving of several devices involving various actors (Ishii, 2013). The concept of Elder Home Care summarizes all practices implemented to support elderly people to continue living independently, despite their disabilities and aging. It constitutes an efficient alternative to reduce the pressure in hospital admissions (Crowley et al., 2016), and give the opportunity to improve elderly care continuity after their discharges from hospitals (Xiao et al. 2018). However, elder hospital care refers to the medical care, diagnostic testing, intensive treatment, or surgeries provided to the patient throughout the hospitalization process. The multiplicity of stakeholders, combined with the dynamic, unstructured information spread over a large amount of information systems, result in a new situation in which decision support systems become essential when making daily operational and collective decisions. Firstly, this paper introduces a decision support Framework that enables home care organizations to deploy their available resources more effectively with a multi-agent system paradigm. The addressed operational collective decision problem concerns the assignment and coordination of home caregivers from different organizations. Secondly, a decision support methodology for intra-hospital care based on quantitative techniques, and statistical method, is proposed. This methodology, allows the evaluation of elderly care pathways behavior
Othmani-Guibourg, Mehdi. "Supervised learning for distribution of centralised multiagent patrolling strategies." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS534.
Full textFor nearly two decades, patrolling has received significant attention from the multiagent community. Multiagent patrolling (MAP) consists in modelling a patrol task to optimise as a multiagent system. The problem of optimising a patrol task is to distribute the most efficiently agents over the area to patrol in space and time, which constitutes a decision-making problem. A range of algorithms based on reactive, cognitive, reinforcement learning, centralised and decentralised strategies, amongst others, have been developed to make such a task ever more efficient. However, the existing patrolling-specific approaches based on supervised learning were still at preliminary stages, although a few works addressed this issue. Central to supervised learning, which is a set of methods and tools that allow inferring new knowledge, is the idea of learning a function mapping any input to an output from a sample of data composed of input-output pairs; learning, in this case, enables the system to generalise to new data never observed before. Until now, the best online MAP strategy, namely without precalculation, has turned out to be a centralised strategy with a coordinator. However, as for any centralised decision process in general, such a strategy is hardly scalable. The purpose of this work is then to develop and implement a new methodology aiming at turning any high-performance centralised strategy into a distributed strategy. Indeed, distributed strategies are by design resilient, more adaptive to changes in the environment, and scalable. In doing so, the centralised decision process, generally represented in MAP by a coordinator, is distributed into patrolling agents by means of supervised learning methods, so that each agent of the resultant distributed strategy tends to capture a part of the algorithm executed by the centralised decision process. The outcome is a new distributed decision-making algorithm based on machine learning. In this dissertation therefore, such a procedure of distribution of centralised strategy is established, then concretely implemented using some artificial neural networks architectures. By doing so, after having exposed the context and motivations of this work, we pose the problematic that led our study. The main multiagent strategies devised until now as part of MAP are then described, particularly a high-performance coordinated strategy, which is the centralised strategy studied in this work, as well as a simple decentralised strategy used as reference for decentralised strategies. Among others, some existing strategies based on supervised learning are also described. Thereafter, the model as well as certain of key concepts of MAP are defined. We also define the methodology laid down to address and study this problematic. This methodology comes in the form of a procedure that allows decentralising any centralised strategy by means of supervised learning. Then, the software ecosystem we developed for the needs of this work is also described, particularly PyTrol a discrete-time simulator dedicated to MAP developed with the aim of performing MAP simulation, to assess strategies and generate data, and MAPTrainer, a framework hinging on the PyTorch machine learning library, dedicated to research in machine learning in the context of MAP
Jacob, Frederique. "la ville méditerranéenne : approche spatiale d'une aire géographique multiculturelle de proximité à travers un concept producteur d'espace : la propreté." Phd thesis, Université de Provence - Aix-Marseille I, 2006. http://tel.archives-ouvertes.fr/tel-00371494.
Full textBelabbès, Sihem. "Contribution aux systèmes de délibération multi-agent : une approche argumentative." Toulouse 3, 2007. http://www.theses.fr/2007TOU30127.
Full textIn a multi-agent system, autonomous agents maintaining reasoning capabilities with possibly contradictory preferences need to interact in order to solve a common problem. As conflicts may arise from their interdependencies, negotiation is a powerful mechanism for finding mutually acceptable compromises for the agents. Three negotiation approaches are distinguished in the literature. The two first approaches procede by an exchange of offers and counter-offers until an acceptable one for the agents is reached. So the agents may reject offers that they would have accepted if those offers were justified by good reasons. Recently a third approach suggests integrating argumentation in negotiation processes. It represents the scope of our work. One advantage of argumentation is in allowing agents to support the exchanged offers by arguments or reasons to believe in them. This may bring the agents to modify their beliefs and/or their preferences, and by consequence to mutually influence each other. In other words, arguments may help agents in their decision-making task by leading them to reconsider their preferences upon offers, which may increase the chances of finding compromises. .
Louati, Amine. "Une approche multi-agents pour la composition de services Web fondée sur la confiance et les réseaux sociaux." Thesis, Paris 9, 2015. http://www.theses.fr/2015PA090035/document.
Full textThis thesis deals with service discovery, selection and composition problems. The aim is to fulfill a complex requester query. To do that, we propose a multi-agent approach based on trust and social networks. We define a trust model as a compositional concept that includes social, expert, recommender and cooperation-based component. The social-based component judges whether or not the provider is worthwhile pursuing before using his services. The expert-based component estimates whether or not the service behaves well and as expected. The recommender-based component checks whether or not an agent is reliable and if we can rely on its recommendations. The cooperation-based component allows agents to decide with whom to interact in a service composition. We propose a distributed algorithm for service discovery using trust between agents and referral systems in social networks. We also develop a new method based on a probabilistic model to infer trust between non adjacent agents while taking into account roles of intermediate agents. Finally, we present an original coalition formation process which is incremental, dynamic and overlapping for service composition in social networks. %In particular, our coalition formation process engaging self-interested agents is incremental, dynamic and overlapping. Experimental results show that our multi-agents approaches are efficient, outperforms existing similar ones and can deliver more trustworthy results at low cost of communications
Novaro, Arianna. "Collective decision-making with goals." Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30179.
Full textAgents having to take a collective decision are often motivated by individual goals. In such scenarios, two key aspects need to be addressed. The first is defining how to select a winning alternative from the expressions of the agents. The second is making sure that agents will not manipulate the outcome. Agents should also be able to state their goals in a way that is expressive, yet not too burdensome. This dissertation studies the aggregation and the strategic component of multi-agent collective decisions where the agents use a compactly represented language. The languages we study are all related to logic: from propositional logic, to generalized CP-nets and linear temporal logic (LTL). Our main contribution is the introduction of the framework of goal-based voting, where agents submit individual goals expressed as formulas of propositional logic. Classical aggregation functions from voting, judgment aggregation, and belief merging are adapted to this setting and studied axiomatically and computationally. Desirable axiomatic properties known in the literature of social choice theory are generalized to this new type of propositional input, as well as the standard complexity problems aimed at determining the result. Another important contribution is the study of the aggregation of generalized CP-nets coming from multiple agents, i.e., CP-nets where the precondition of the preference statement is a propositional formula. We use different aggregators to obtain a collective ordering of the possible outcomes. Thanks to this thesis, two lines of research are thus bridged: the one on the aggregation of complete CP-nets, and the one on the generalization of CP-nets to incomplete preconditions. We also contribute to the study of strategic behavior in both collective decision-making and game-theoretic settings. The framework of goal-based voting is studied again under the assumption that agents can now decide to submit an untruthful goal if by doing so they can get a better outcome. The focus is on three majoritarian voting rules which are found to be manipulable. Therefore, we study restrictions on both the language of the goals and on the strategies allowed to the agents to discover islands of strategy-proofness. We also present a game-theoretic extension of a recent model of opinion diffusion over networks of influence. In the influence games defined here, agents hold goals expressed as formulas of LTL and they can choose whether to use their influence power to make sure that their goal is satisfied. Classical solution concepts such as weak dominance and winning strategy are studied for influence games, in relation to the structure of the network and the goals of the agents. Finally, we introduce a novel class of concurrent game structures (CGS) in which agents can have shared control over a set of propositional variables. Such structures are used for the interpretation of formulas of alternating-time temporal logic, thanks to which we can express the existence of a winning strategy for an agent in a repeated game (as, for instance, the influence games mentioned above). The main result shows by means of a clever construction that a CGS with shared control can be represented as a CGS with exclusive control. In conclusion, this thesis provides a valuable contribution to the field of collective decision-making by introducing a novel framework of voting based on individual propositional goals, it studies for the first time the aggregation of generalized CP-nets, it extends a framework of opinion diffusion by modelling rational agents who use their influence power as they see fit, and it provides a reduction of shared to exclusive control in CGS for the interpretation of logics of strategic reasoning. By using different logical languages, agents can thus express their goals and preferences over the decision to be taken, and desirable properties of the decision process can be ensured