Energy is consumed every day at home as we perform simple tasks, such as watching television, washing dishes and heating/cooling home spaces during season of extreme weather conditions, using appliances, or turning on lights. Most often, the energy resources used in residential systems are obtained from natural gas, coal and oil. Moreover, climate change has increased awareness of a need for expendable, energy resources. As a result, carbon dioxide emissions are increasing and creating a negative effect on our environment and on our health. In fact, growing energy demands and limited natural resource might have negative impacts on our future. Therefore, saving energy is becoming an important issue in our society and it is receiving more attention from the research community. This thesis introduces a intelligent energy controller algorithm based on software agent approach that reduce the energy consumption at home for both heating and cooling spaces by considering the user’s occupancy, outdoor temperature and user’s preferences as input to the system. Thus the proposed approach takes into consideration the occupant’s preferred temperature, the occupied and unoccupied spaces, as well as the time spent in each area of the home. A Java based simulator has been implemented to simulate the algorithm for saving energy in heating and cooling systems. The results from the simulator are compared to the results of using HOT2000, which is Canada’s leading residential energy analysis and rating software developed by CanmetENERGY’s Housing, Buildings, Communities and Simulation (HBCS) group. We have calculated how much energy a home modelled will use under emulated conditions. The results showed that the implementation of the proposed energy controller algorithm can save up to 50% in energy consumption in homes dedicated to heating and cooling systems compared to the results obtained by using HOT2000.

Thesis is to Introduce an Intelligent cross platform architecture with Multi-agent system in order to equip the simulation Models with agents, having intelligent behavior, reactive and pro-active nature and rational in decision making.

In this thesis, we discuss models for multi-agent dynamical systems. We study the tracking/migration problem for flocks and a theoretical framework for design and analysis of flocking algorithm is presented. The interactions between agents in the systems are denoted by potential functions that act as distance functions, hence, the design of proper potential functions are crucial in modelling and analyzing the flocking problem for multi-agent dynamical systems. Constructions for both non-smooth potential functions and smooth potential functions with finite cut-off are investigated in detail. The main contributions of this thesis are to extend the literature of continuous flocking models with impulsive control and delay. Lyapunov function techniques and techniques for stability of continuous and impulsive switching system are used, we study the asymptotic stability of the equilibrium of our models with impulsive control and discovery that by applying impulsive control to Olfati-Saber's continuous model, we can remove the damping term and improve the performance by avoiding the deficiency caused by time delay in velocity sensing. Additionally, we discuss both free-flocking and constrained-flocking algorithm for multi-agent dynamical system, we extend literature results by applying velocity feedbacks which are given by the dynamical obstacles in the environment to our impulsive control and successfully lead to flocking with obstacle avoidance capability in a more energy-efficient way. Simulations are given to support our results, some conclusions are made and future directions are given.

In this thesis, I propose an agent-based cooperative model for supply chains to commit orders by satisfying constraints. Due to the limitation of the real world environment, the centralized schedule model to handle constraint satisfaction is impractical, it is important to excise the distributed constraint satisfaction model to meet the outsourcing paradigm of supply chain management. I introduce a multi-agent system based coordination mechanism that integrates theories of negotiation and distributed constraint satisfaction problem to resolve the constraints in supply chain. I adopt the asynchronous weak-commitment search, a DCSP algorithm to resolve the global constraint in supply chain. Asynchronous weak-commitment search is complete backtracking algorithms that guarantee to find a solution if there is a solution existing and asynchronous weak-commitment search provide priority dynamic mechanism that help us to find a solution quickly than other backtracking algorithms. We construct a coordination agent for each business entity in supplier chain. The agent embedded in the ability to resolve the constraints autonomously. We expect this agent-based coordination mechanism can make supply chain more efficient and enhance supply chain's agility.

In the thesis, we provide a solution to solve a schema change problem. In a data warehouse system, if schema changes occur in a data source, the overall system will lose the consistency between the data sources and the data warehouse. These schema changes will render the data warehouse obsolete. We have developed three stages to handle schema changes occurring in databases. They are change detection, diagnosis, and handling. Recommendations are generated by DB-agent to information DW-agent to notify the DBA what and where a schema change affects the star schema. In the study, we mainly handle seven schema changes in a relational database. All of them, we not only handle non-adding schema changes but also handling adding schema changes. A non-adding schema change in our experiment has high correct mapping rate as using a traditional mappings between a data warehouse and a database. For an adding schema change, it has many uncertainties to diagnosis and handle. For this reason, we compare similarity between an adding relation or attribute and the ontology concept or concept attribute to generate a good recommendation. The evaluation results show that the proposed approach is capable to detect these schema changes correctly and to recommend the DBA about the changes appropriately.

With rapid development of information technology, the company can find and communicate with new partners easily, which makes the relation more complex and unstable. How to improve the performance of the supply chain is an important issue. In this study, we try to discuss the problem from the three factors including switching cost, trust and information sharing. First, we propose a conceptual model of switching cost, trust, information sharing and supply chain performance. The performance indexes include the average fulfillment rate, average stock cost, and average cycle time. Second, in order to verify the model, we construct a simulation environment of supply chain and construct a decision mechanism based on the conceptual model. Final, we observe the effect and variation of the different order demand environment, the different information sharing threshold, different propensity of switching cost and trust, and different product price and different producing technology.

Heterogeneous multi-agent systems are currently used in a wide variety of situations, including search and rescue, military applications, and off-world exploration, however it is difficult to understand the actions of these systems or naturalistically assign these mixed teams to tasks. These agents, which may be human, robot or software, have different capabilities but will need to coordinate effectively with humans in order to operate. The first and largest contributing factor to this challenge is the processing, understanding and representing of elements of the natural world in a manner that can be utilized by artificial agents. A second contributing factor is that current abstractions and robot architectures are ill-suited to address this problem. This dissertation addresses the lack of a high-level abstraction for the naturalistic coordination of teams of heterogeneous robots, humans and other agents through the development of roles. Roles are a fundamental concept of social science that may provide this necessary abstraction. Roles are not a new concept and have been used in a number of related areas. This work draws from these fields and constructs a coherent and usable model of roles for robotics. This research is focussed on answering the following question: Can the use of social roles enable the naturalistic coordinated operation of robots in a mixed setting? In addition to this primary question, related research includes defining the key concepts important to artificial systems, providing a mapping and implementation from these concepts to a usable robot framework and identifies a set of robot-specific roles used for human-robot interaction. This research will benefit both the artificial intelligence agent and robotics communities. It poses a fundamental contribution to the multi-agent community because it extends and refines the role concept. The application of roles in a principled and complete implementation is a novel contribution to both software and robotic agents. The creation of an open source operational architecture which supports taskable robots is also a major contribution.

Η διατριβή ασχολείται με το πρόβλημα της διαλειτουργικότητας και συνεργασίας εκπαιδευτικών εφαρμογών στο διαδίκτυο. Η έρευνα οδήγησε στη σχεδίαση και υλοποίηση ενός πρωτότυπου περιβάλλοντος που στηρίζεται στην αρχιτεκτονική πολλαπλών πρακτόρων και επιτρέπει τη συνεργασία μεταξύ των εκαπιδευτικών κόμβων να υποστηρίξουν μαθησιακές δυσκολίες του από απόσταση εκπαιδευομένου. / This thesis focuses on the problem of the interoperability an d cooperation between educational applications in the open enviroment of the World Wide Web. The research led to the design and development of a prototype enviroment (Multi Agent Tutoring System MATS) that implements the collaboration among educational nodes in order to support the needs of a distantr learner.

The work presented in this PhD thesis defines a new approach for the modeling and the conceptualization of enterprise business processes in the perspective of building intelligent assistance software tools to support these processes. The proposed approach defines an organizational ontology, named K-CRIO. Its description is based on the Ontology Web Language. To illustrate our work, an intelligent assistance system has been designed and implemented according to the result from the modeling and conceptualization of a specific business process with the K-CRIO Ontology. It is a web-based application that integrates and takes full advantage of multi-agent systems.The K-CRIO Ontology is an Ontology dedicated to the study of organizations and the analysis of business processes adopting an organizational point of view. Specifically, it is used to understand, analyze and reason about organizations and the processes they implement. The targeted organizations are those composed of entities involved throughout products' design and, to do so, following a defined business process. The range of this type of organizations is quite wide. We have thus limited our study to organizations that produce software as the final process goal, specifically IT enterprises delivering software products or services. In this context, the K-CRIO ontology could be used to model structure of the considered organizations and model human activities appearing in their business processes. This ontology could be used to support process assistance within the described organizations. More specifically, the ontology could provide means for reasoning, annotating resources, monitoring design processes, enabling searches and pro-actively proposing tips and proper content. In order to illustrate the usage of K-CRIO, we apply K-CRIO on two different processes: the Waterfall Model and the Scrum methodology. These examples are both classical software-development processes. Moreover, for Scrum, the famous agile software-development process widely used in software enterprises, we have designed and developed an intelligent assistance tool. This tool mainly helps Scrum Masters to make decision by monitoring Scrum project teams' activities within their various projects and collecting knowledge about these activities.

Les agents situés dans l'image fournissent un cadre privilégié pour la mise en oeuvre de stratégies coopératives et localement adaptées en segmentation d'image. Ils facilitent l'intégration des connaissances a priori, expressions d'un modèle, permettant ainsi de dégager de nouvelles contraintes indispensables à toutes les étapes de la vision par ordinateur (de la segmentation à l'interprétation). Nous proposons un cadre conceptuel pour l'architecture logicielle d'un système de vision bas-niveau basée sur des agents situés dans l'image. Une telle architecture est articulée en trois niveaux d'analyse et de description : 1. Description globale et structurelle de l'organisation regroupant les agents. Cette étape de description s'attache à établir les liens entre agents. Nous proposons comme élément organisationnel la pyramide irrégulière qui impose sa structure à la population d'agents, afin de garantir un comportement globalement contrôlable et convergent de ces derniers. 2. Description locale, fonctionnelle et comportementale des agents composant le système. Nous proposons une mise en oeuvre particulière de l'architecture logicielle de vision bas-niveau. Dans cette dernière, deux familles d'agents, qui traduisent des primitives région et contour, interagissent localement au sein de la pyramide. Notre objectif est de montrer comment cette méthodologie permet une implémentation riche, flexible et distribuée des aspects précédemment identifiés; à savoir : l'adaptation locale, l'intégration et l'expression d'incertitudes dans l'information a priori et des traitements coopératifs région/région et région/contour. 3. Finalement, une analyse globale, comparative et fonctionnelle vérifie que l'ensemble des interactions locales produit une bonne segmentation des images. Nous comparons notre approche avec d'autres méthodes de segmentation sur des images médicales et des images de synthèse.