Software agents and multi-agent systems (MAS) have grown into a very active area of research and commercial development activity. There are many current emerging real-world applications spanning multitude of diverse domains. In the context of agents, ontology has been widely recognised for their significant benefits to interoperability, reusability, and both development and operational aspects of agent systems and applications. Ontology-based multi-agent systems (OBMAS) exploit these advantages in providing intelligent and semantically aware applications. In addressing the lack of support for ontology in existing methodologies for multi-agent development, this thesis proposes a design methodology for the building of such intelligent multi-agent applications called MOMA. This alternative approach focuses on the development of ontology as the driving force of the development process. By allowing the domain and characteristics of utilisation and experimentation to be dictated through ontology, researchers and domain experts can specify the agent application without any knowledge of agent design and lower level programming. Through the use of a structured ontology model and the use of integrated tools, this approach contributes towards the building of semantically aware intelligent applications for use by researchers and domain experts. MOMA is evaluated through case studies in two different domains: financial services and e-Health.

The cooperative control of large-scale multi-agent systems has gained a significant interest in recent years from the robotics and control communities for multi-vehicle control. One motivator for the growing interest is the application of spatially and temporally distributed multiple unmanned aerial vehicle (UAV) systems for distributed sensing and collaborative operations. In this research, the multi-vehicle control problem is addressed using a decentralised control system. The work aims to provide a decentralised control framework that synthesises the self-organised and coordinated behaviour of natural swarming systems into cooperative UAV systems. The control system design framework is generalised for application into various other multi-agent systems including cellular robotics, ad-hoc communication networks, and modular smart-structures. The approach involves identifying suitable relationships that describe the behaviour of the UAVs within the swarm and the interactions of these behaviours to produce purposeful high-level actions for system operators. A major focus concerning the research involves the development of suitable analytical tools that decomposes the general swarm behaviours to the local vehicle level. The control problem is approached using two-levels of abstraction; the supervisory level, and the local vehicle level. Geometric control techniques based on differential geometry are used at the supervisory level to reduce the control problem to a small set of permutation and size invariant abstract descriptors. The abstract descriptors provide an open-loop optimal state and control trajectory for the collective swarm and are used to describe the intentions of the vehicles. Decentralised optimal control is implemented at the local vehicle level to synthesise self-organised and cooperative behaviour. A deliberative control scheme is implemented at the local vehicle level that demonstrates autonomous, cooperative and optimal behaviour whilst the preserv ing precision and reliability at the local vehicle level.

Software agents and multi-agent systems (MAS) have grown into a very active area of research and commercial development activity. There are many current emerging real-world applications spanning multitude of diverse domains. In the context of agents, ontology has been widely recognised for their significant benefits to interoperability, reusability, and both development and operational aspects of agent systems and applications. Ontology-based multi-agent systems (OBMAS) exploit these advantages in providing intelligent and semantically aware applications. In addressing the lack of support for ontology in existing methodologies for multi-agent development, this thesis proposes a design methodology for the building of such intelligent multi-agent applications called MOMA. This alternative approach focuses on the development of ontology as the driving force of the development process. By allowing the domain and characteristics of utilisation and experimentation to be dictated through ontology, researchers and domain experts can specify the agent application without any knowledge of agent design and lower level programming. Through the use of a structured ontology model and the use of integrated tools, this approach contributes towards the building of semantically aware intelligent applications for use by researchers and domain experts. MOMA is evaluated through case studies in two different domains: financial services and e-Health.

Covert channel attacks utilize shared resources to indirectly transmit sensitive information to unauthorized parties. Many current operating systems, such as SELinux, rely on generating labels based on a file's security classification and system-wide security policies and then binding these labels to all such files in the filesystem. Enforcement of security policies in such systems occurs at the time of access to a file or resource. Such mechanisms are flawed, however, in that they do not adequately protect against information laundering by means of covert channels. One recent development, Colored Linux, serves as an extension to SELinux and utilizes watermarking algorithms to "color" the contents of files with their respective security classification in order to enhance resistance to information laundering attacks. In this thesis, a mobile agent-based approach to implementing Colored Linux is proposed to automate the process of detecting and coloring receptive hosts' filesystems and to provide monitoring of the colored filesystem for instances of potential information leakage. Implementation details and execution results are included to illustrate the merits of the proposed approach. An evaluation of the performance of this agent-based system is conducted over a single host as well as a local network of machines and detailed here as well. Finally, third-party analysis of the agent system using formal methods is discussed.

Multi-agent systems rely heavily on coordination and cooperation to achieve a variety of tasks. It is often assumed that these agents will be fully cooperative, or have reliable and equal performance among group members. Instead, we consider cooperation as a spectrum of possible interactions, ranging from performance variations within the group to adversarial agents. This thesis examines several scenarios where cooperation and performance are not guaranteed. Potential applications include sensor coverage, emergency response, wildlife management, tracking, and surveillance. We use geometric methods, such as Voronoi tessellations, for design insight and Lyapunov-based stability theory to analyze our proposed controllers. Performance is verified through simulations and experiments on a variety of ground and aerial robotic platforms. First, we consider the problem of Voronoi-based coverage control, where a group of robots must spread out over an environment to provide coverage. Our approach adapts online to sensing and actuation performance variations with the group. The robots have no prior knowledge of their relative performance, and in a distributed fashion, compensate by assigning weaker robots a smaller portion of the environment. Next, we consider the problem of multi-agent herding, akin to shepherding. Here, a group of dog-like robots must drive a herd of non-cooperative sheep-like agents around the environment. Our key insight in designing the control laws for the herders is to enforce geometrical relationships that allow for the combined system dynamics to reduce to a single nonholonomic vehicle. We also investigate the cooperative pursuit of an evader by a group of quadrotors in an environment with no-fly zones. While the pursuers cannot enter the no-fly zones, the evader moves freely through the zones to avoid capture. Using tools for Voronoi-based coverage control, we provide an algorithm to distribute the pursuers around the zone's boundary and minimize capture time once the evader emerges. Finally, we present an algorithm for the guaranteed capture of multiple evaders by one or more pursuers in a bounded, convex environment. The pursuers utilize properties of the evader's Voronoi cell to choose a control strategy that minimizes the safe-reachable area of the evader, which in turn leads to the evader's capture.

This overview report comprises two projects linked by the theme of the application of intelligent agents. The first project covers the development of RAPIDO, a rapid prototyping toolkit for the development and evaluation of agent applications. The papers and technical reports included for this project look at the implementation and application of the RAPIDO toolkit to a specific test case for evaluation purposes. The second project considers the use of an agent-based simulation of the Internet, called WebAgent, to explore agent-based solutions to improving network performance. The publications present the experimental methodology of WebAgent, and the results of evaluating Expl, an adaptive agent for intelligent control of dynamic caching strategies for web servers and clients. The knowledge gained during the course of these two projects has been published in refereed papers included within the accompanying portfolio. The production of Multi- Agent Systems (MAS), particularly Distributed Artificial Intelligence (DAI) applications, is dependent upon the underlying paradigm. The generic approach to the specification of agent applications, and the object-oriented rapid prototyping technique, have allowed different implementations of a specific problem domain to be evaluated in order to determine the best architecture. The application of agent-based simulation to the field of web document caching has both introduced a new tool for performing evaluations of such techniques and has helped towards the proposal of a new approach, based upon intelligent, adaptive agents. The future of such directions promises to offer far greater application of these ideas to the regulation and management of networks in general.

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.

Musical Agents are an emerging technology, designed to provide a range of new musical opportunities to human musicians and composers. Current systems in this area lack certain features which are necessary for a high quality musician; in particular, they lack the ability to structure their output in terms of a communicative dialogue, and reason about the responses of their partners. In order to address these issues, this thesis develops Musical Act Theory (MAT). This is a novel theory, which models musical interactions between agents, allowing a dialogue oriented analysis of music, and an exploration of intention and communication in the context of musical performance. The work here can be separated into four main contributions: a specification for a Musical Middleware system, which can be implemented computationally, and allows distributed agents to collaborate on music in real-time; a computational model of musical interaction, which allows musical agents to analyse the playing of others as part of a communicative process, and formalises the workings of the Musical Middleware system; MAMA, a musical agent system which embodies this theory, and which can function in a variety of Musical Middleware applications; a pilot experiment which explores the use of MAMA and the utility of MAT under controlled conditions. It is found that the Musical Middleware architecture is computationally implementable, and allows for a system which can respond to both direct musical communi- cation and extramusical inputs, including the use of a custom-built tangible interface. MAT is found to capture certain aspects of music which are of interest — an intuitive notion of performative actions in music, and an existing model of musical interaction. Finally, the fact that a number of different levels — theory, architecture and implementation — are tied together gives a coherent model which can be applied to many computational musical situations.

Published Article / Radio-frequency Identification (RFID) technology promises to revolutionize business processes. While RFID technology is improving rapidly, a reliable deployment of this technology is still a significant challenge impeding its widespread adoption. In this paper we provide a brief overview of some common fundamental characteristics of RFID data and devices, which pose significant challenges in the design of RFID middleware systems. In addition, the development of a multi-agent RFID middleware solution to address the RFID data and device management challenges is discussed.