Etablir le meilleur plan pour l'usinage d'un produit, le meilleur ordonnancement des activités de construction d'un bâtiment ou la meilleure tournée de véhicules pour la livraison des commandes, en prenant en compte diverses contraintes économiques, temporelles, humaines, ou même météorologiques : dans cette diversité d'applications, optimiser la planification est une tâche complexe par le grand nombre d'entités hétérogènes en interaction, la forte dynamique, les objectifs contradictoires à atteindre, etc. La planification de missions pour des constellations de satellites en est un exemple majeur : beaucoup de paramètres et de contraintes, souvent antagonistes, doivent être pris en compte, entraînant une importante combinatoire. Actuellement, en Europe, les plans de missions sont élaborés au sol, juste avant que le satellite ne soit visible par la station d'émission. Les requêtes arrivant durant la planification ne peuvent être traitées, et sont mises en attente. De plus, la complexité de ce problème croit drastiquement : le nombre de constellations et les satellites les composant augmentent, ainsi que le nombre de requêtes journalières. Les approches actuelles montrent leurs limites. Pour pallier à ces inconvénients, de nouveaux systèmes basés sur la décentralisation et la distribution inhérentes à ce genre de problèmes, sont nécessaires. La théorie des systèmes multi-agents adaptatifs (AMAS) et notamment le modèle AMAS4Opt (AMAS for Optimisation) ont montré leur adéquation pour la résolution de problèmes d'optimisation complexes sous contraintes. Le comportement local et coopératif des agents AMAS permet au système de s'auto-adapter à la forte dynamique et de fournir des solutions adéquates rapidement. Dans cette thèse, nous adressons la résolution de la planification des missions de satellites par AMAS. Pour cela, nous avons complété et enrichi les modèles d'agents proposés par AMAS4Opt. Nous avons ainsi développé le système de planification dynamique de missions ATLAS. Pour valider ATLAS sur divers critères, nous avons utilisé un grand nombre de données hétérogènes. Enfin, ce travail a été comparé à un système " opérationnel' " standard sur des scénarios réels, mettant en valeur les apports de notre système. / Building the best plan in product treatment, the best schedule to a building construction or the best route for a salesman in order to visit a maximum of cities in the time allowed while taking into account different constraints (economic, temporal, humans or meteorological ): in all of those variety of applications, optimizing the planning is a complex task including a huge number of heterogeneous entities in interaction, the strong dynamics, multiple contradictory objectives, etc. Mission planning for constellations of satellites is a major example: a lot of parameters and constraints, often antagonists must be integrated, leading to an important combinatorial search space. Currently, in Europe, plans are built on ground, just before the satellite is visible by the ground stations. Any request coming during the planning process must wait for the next period. Moreover, the complexity of this problem grows drastically: the number of constellations and satellites increases, as the number of daily requests. Current approaches have shown their limits. To overcome those drawbacks, new systems based on decentralization and distribution inherent to this problem, are needed. The adaptive multi-agent systems (AMAS) theory and especially the AMAS4Opt (AMAS For Optimization) model have shown their adequacy in complex optimization problems solving. The local and cooperative behavior of agents allows the system to self-adapt to highly dynamic environments and to quickly deliver adequate solutions. In this thesis, we focus on solving mission planning for satellite constellations using AMAS. Thus, we propose several enhancement for the agent models proposed by AMAS4Opt. Then, we design the ATLAS dynamic mission planning system. To validate ATLAS on several criteria, we rely on huge sets of heterogeneous data. Finally, this work is compared to an operational and standard system on real scenarios, highlighting the value of our system.

No description available.

Helicobacter pylori is a Gram-negative bacterium that is the major cause of many upper gastrointestinal diseases such as gastritis and peptic ulcer disease. It has the unique ability of colonising the human gastric mucosa. Failure in complete eradication of H. pylori in infected patients, mainly due to antibiotic resistance, has necessitated the development of better therapeutics, especially from natural sources. In this study, extract of Maris piper potatoes were obtained and evaluated for antibacterial activity against H. pylori in vitro. Antibacterial activity was carried out against antibiotic-sensitive and clinical antibiotic-resistant H. pylori strains, as well as a range of Gram-negative bacteria including Helicobacter and Campylobacter species, using the viable count method. Result of the antibacterial assays indicated that potato extract is bactericidal against H. pylori lab strain as well as clinical antibiotic-resistant strains, with minimum inhibitory concentration at 15.6 mg/ml. Potato extract also showed minimal antibacterial activity against other Gram- negative bacteria tested, with minimum inhibitory concentration at 250 mg/ml. The effect of the extract on the morphology of H. pylori was also observed by transmission electron microscopy (TEM). TEM analysis of potato extract-treated H. pylori cells showed disruption of the morphology of H. pylori, characterized by separation of the outer membrane from the inner membrane and loss of cell shape. Potato extract also caused hyperpolarisation of H. pylori plasma membrane; however it is unclear whether the membrane active pumping activity is affected. Mutants of H. pylori that are resistant to potato extract were generated as a means to identify the target of potato extract within the H. pylori genome. Genome sequence analysis led to the discovery of a hypothetical protein, encoded by HP0603 gene, which may be involved in inducing resistance to potato extract. The results obtained in this study provide great insights into the anti-H. pylori activity of potato extract. Overall, this study suggests the potential use of potato extract as a source of anti-H. pylori agents; and stimulates further studies into identifying its mechanism of action.

This thesis applies predictor-based methods for the distributed consensus control of multi-agent systems with input delay. "Multi-agent systems" is a term used to describe a group of agents which are connected together to achieve specified control tasks over a communication network. In many applications, the subsystems or agents are required to reach an agreement upon certain quantities of interest, which is referred to as "consensus control". This input delay may represent delays in the network communication. The main contribution of this thesis is to provide feasible methods to deal with the consensus control for general multi-agent systems with input delay. The consensus control for general linear multi-agent systems with parameter uncertainties and input delay is first investigated under directed network connection. Artstein reduction method is applied to deal with the input delay. By transforming the Laplacian matrix into the real Jordan form, delay-dependent conditions are derived to guarantee the robust consensus control for uncertain multi-agent systems with input delay. Then, the results are extended to a class of Lipschitz nonlinear multi-agent systems and the impacts of Lipschitz nonlinearity and input delay in consensus control are investigated. By using tools from control theory and graph theory, sufficient conditions based on the Lipschitz constant are identified for proposed protocols to tackle the nonlinear terms in the system dynamics. Other than the time delay, external disturbances are inevitable in various practical systems including the multi-agent systems. The consensus disturbance rejection problems are investigated. For linear multi-agent systems with bounded external disturbances, Truncated Predictor Feedback (TPF) approach is applied to deal with the input delay and the H_infinity consensus analysis is put in the framework of Lyapunov analysis. Sufficient conditions are derived to guarantee the H_infinity consensus in time domain. Some disturbances in real engineering problems have inherent characteristics such as harmonics and unknown constant load. For those kinds of disturbances in Lipschitz nonlinear multi-agent systems with input delay, Disturbance Observer-Based Control (DOBC) technique is applied to design the disturbance observers. A new predictor-based control scheme is constructed for each agent by utilizing the estimate of the disturbance and the prediction of the relative state information. Sufficient delay-dependent conditions are derived to guarantee consensus with disturbance rejection.

La Tarification à l’Activité (T2A) contraint les services d’urgences hospitalières à développer différentes stratégies d’'allocation efficiente des ressources. L'optimisation de la prise en charge est centrale à cette problématique et vise des coûts de production couverts par les revenus induits par la T2A. Aussi, l'objectif de la thèse est d’identifier l’apport d’un Système d’Aide à la Décision (SAD) basé sur les Systèmes Multi-Agents (SMA) utilisant une modélisation basée sur un algorithme d'ordonnancement des moyens de production des soins en trois phases (OR-3P). Cette modélisation formalise l'organisation de ces services autour de cinq types d'agents. L’Agent Ordonnanceur y chargé d’affecter les personnels de l’équipe médicale et de gérer les flux de patients. Il joue un rôle prépondérant dans la recherche d’optimisation. Les résultats obtenus de l’application simulée de l’OR-3P, montrent l’optimisation des délais d’attente et de passage global, une augmentation de la productivité et une indication qualitative du bon fonctionnement de la prise en charge. Ces résultats incitent à réaliser des expérimentations dans des établissements français. / The activity-based payment, which is known in France as T2A requires hospital emergency departments, faced with a very strong growth in their activities since 1990, to develop strategies of an efficient allocation of resources. The optimization of medical treatment is central to this issue and should allow obtaining production costs covered by funding induced T2A. The main objective of the thesis was to identify the contribution of a System Decision Support (DSS) based on Multi-Agent Systems (MAS), using multi-agent modelling of care means production, using a three-phase scheduling algorithm, so called OR-3P. This modelling formalizes the organization of emergency departments around five types of agent. The scheduler Officer is responsible for assigning personnel to the medical team in an efficient framework for managing patient flow, plays the leading role in the search of optimized management. Results from the application of OR-3P, show an optimizing of the delays and the overall passage, an increase in productivity, a qualitative indication of proper functioning. These results lead to tests in French institutions.

Le contexte informationnel dans lequel évolue un agent possède une importance extrême quandcelui-ci élabore son comportement futur. Un agent rationnel doit en effet baser ses choix sur les informationsqu’il possède pour choisir ses actions. Or, dans les applications réelles, l’information disponible àl’agent est souvent rare et peu précise. De multiples modèles ont été élaborés dans les différents cadresd’application de l’intelligence artificielle afin de caractériser une décision rationnelle dans chacun descontextes informationnels possibles. Les travaux présentés dans cette thèse concernent l’élaboration d’unmodèle permettant à un agent de prendre des décisions rationnelles dans un contexte informationnel trèspauvre. La seule information dont dispose un agent à propos du résultat de ses actions est la donnée del’ensemble de résultats de chacune d’entre elles. En particulier, aucune information sur la conséquence laplus susceptible de se produire n’est disponible. L’agent est supposé égoïste (au sens où seul compte pourlui son propre intérêt) et autonome. Il évolue de plus dans un environnement où il coexiste avec d’autresagents (qui sont aussi égoïstes et autonomes). Les actions d’un agent influent sur les autres agents. Ladémarche entreprise pour élaborer le modèle est la suivante. D’abord, nous caractérisons les critères dedécision rationnels d’un agent seul dans le contexte informatif étudié. Ensuite, nous étendons ces critèresde décision individuelle au cas multi-agent en nous appuyant sur la théorie des jeux qui est le meilleurcadre pour exprimer les interactions entre agents rationnels et en particulier les possibilités de coordinationentre les agents. Enfin, le domaine de la planification est un excellent cadre pour représenter etexprimer les concepts du modèle. / The informative context in which an agent evolves is extremely important when she elaborates her futurebehaviour. A rational agent must base her choices on the available information. In realistic applications,the information is often rare and imprecise. Many models have been introduced to caracterize rationaldecision in each possible informative context. This thesis is about the elaboration of a model that allowsan agent to make rational decisions in an extremely poor informative context. The only informationthat is available to an agent about her actions’ consequences is the result set of each of her actions. Noinformation about which consequence of any action will eventually happen is available. The agent issupposed to be selfish (which means that her own interest is her only concern) and autonomous. Sheevolves in an environment in which she coexists with other agents (that are as selfish and autonomous asher). An agent action may inflence those of other agents. We used the following approach to build ourmodel. First, we caracterized the rational decision criteria for an agent to use in the context of completeignorance. Then we extended these criteria, by using game theory concepts, to a multiagent environment.Finally, the planning framework is an excellent framework to represent the introduced concepts.

The thesis is describing agent in limited liability company. First part is about the company in general, second about the steps that has to be taken before becomming and agent and also how the post can be disolve and then main part of the thesis is focused on the rights and obligations of an agent.

The main objective of this thesis is to integrate agent oriented concepts into a complex methodology for description of business processes MMABP that is being developed on University of Economics, Prague. The first part describes and explains agent oriented approaches to business process modeling (i*/TROPOS, AOR, OOEM and UFO ontology) and demonstrates them on a case study. MMABP methodology is then compared with these approaches and evaluated. The evaluation concludes that MMABP is incomplete in relation to agent oriented concepts of plan, plan execution, desire, intention, commitment and claim and also to concepts of stable and unstable state. Concepts of goal, agent and business process are evaluated as inaccurate. Second part of the theses arguments and defines MMABP extension that eliminates identified inadequacies. Metamodel is amended with the concept of plan execution which is intentionally executed action that leads to a goal fulfillment. Plan is a description of this special kind of action. Agent is an entity that has goals and is capable of executing plans. Business process received a new definition and is defined as something that defines plans (as a prescription of actions), has goals and uses agents to execute actions. Business process is not defined as a specialization of a complex event anymore. The thesis also specifies procedure where concepts are step-by-step transformed from one diagram to another.

It is claimed that action discourse provides us with a criterion of adequacy for a theory of action; that with action discourse we have a family of concepts which a theory of action must accommodate. After an exegesis of Davidson's essay "Agency", it is argued that his semantics of action is incompatible with our concepts of motivation and responsibility for action and of attributions of action and agency, and must, therefore, be rejected. A theory of rational agency is presented within which are to be found accounts of intention, coming to intend, intentional action, and an alternative semantics of action which connects the action essentially to agency. The theory of rational agency is then used to illuminate the concepts of trying, compulsion, autonomy and involuntariness, mistake, accident, and the so-called active-passive distinction. / Arts, Faculty of / Philosophy, Department of / Graduate

As technology advances, many practical applications require human-controlled robots. For such applications, it is useful to determine the optimal number of robots an operator should control to maximize human efficiency given different situations. One way to achieve this is through computer simulations of team performance. In order to factor in various parameters that may affect team performance, an agent-based model will be used. Agent-based modeling is a computational method that enables a researcher to create, analyze, and experiment with models composed of agents that interact within an environment [12]. We construct an agent-based model of humans interacting with robots, and explore how team performance relates to different agent parameters and team organizational structures [21]. Prior work describes interaction between a single operator and multiple robots, while this work includes multi-operator performance and coordination. Model parameters include neglect time, interaction time, operator slack time, level of robot autonomy, etc. Understanding the parameters that influence team performance will be a step towards finding ways to maximize performance in real life human-robot systems.