This thesis proposed solutions to some shortcomings to current eLearning architectures. The proposed DeLC architecture supports context-aware and adaptable provision of eLearning services and electronic content. The architecture is fully distributed and integrates service-oriented development with agent technology. Central to this architecture is that a node is our unit of computation (known as eLearning node) which can have purely service-oriented architecture, agent-oriented architecture or mixed architecture. Three eLeaerning Nodes have been implemented in order to demonstrate the vitality of the DeLC concept. The Mobile eLearning Node uses a three-level communication network, called InfoStations network, supporting mobile service provision. The services, displayed on this node, are to be aware of its context, gather required learning material and adapted to the learner request. This is supported trough a multi-layered hybrid (service- and agent-oriented) architecture whose kernel is implemented as middleware. For testing of the middleware a simulation environment has been developed. In addition, the DeLC development approach is proposed. The second eLearning node has been implemented as Education Portal. The architecture of this node is poorly service-oriented and it adopts a client-server architecture. In the education portal, there are incorporated education services and system services, called engines. The electronic content is kept in Digital Libraries. Furthermore, in order to facilitate content creators in DeLC, the environment Selbo2 was developed. The environment allows for creating new content, editing available content, as well as generating educational units out of preexisting standardized elements. In the last two years, the portal is used in actual education at the Faculty of Mathematics and Informatics, University of Plovdiv. The third eLearning node, known as Agent Village, exhibits a purely agent-oriented architecture. The purpose of this node is to provide intelligent assistance to the services deployed on the Education Pportal. Currently, two kinds of assistants are implemented in the node - eTesting Assistants and Refactoring eLearning Environment (ReLE). A more complex architecture, known as Education Cluster, is presented in this thesis as well. The Education Cluster incorporates two eLearning nodes, namely the Education Portal and the Agent Village. eLearning services and intelligent agents interact in the cluster.

published_or_final_version / abstract / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

Peer-to-Peer (P2P) networks have seen tremendous growth in development and usage in recent times. This attention has brought many developments as well as new challenges to these networks. We will show that agent extensions to P2P networks offer solutions to many problems faced by P2P networks. In this research, an attempt is made to bring together JXTA P2P infrastructure and Jinni, a Prolog based agent engine to form an agent based P2P network. On top of the JXTA, we define simple Java API providing P2P services for agent programming constructs. Jinni is deployed on this JXTA network using an automated code update mechanism. Experiments are conducted on this Jinni/JXTA platform to implement a simple agent communication and data exchange protocol.

D.Phil. / A modern day N-P complete problem is the assigning of frequencies to transmitters in a cellular network in such a manner that, ideally, no two transmitters in the same cell or neighbouring cells use the same frequency. Considering that an average cellular network provider has over 29 000 transmitters and only 55 frequencies, choosing these frequencies in an optimal way is a very difficult computational problem. Swarm intelligence allows the acceptable minimization and optimization of the frequency assignment problem (FAP). Swarm intelligence is a concept modelling the processes in natural systems such as ant colonies, beehives, human immune systems and the human brain. These systems are selforganizational and display high efficiency in the execution of their tasks. A number of simple automated agents interacting with each other and the environment form a collective. Specifically, there is no "central agent" directing the others. A collective can display surprising intelligence which emerges out of the interaction of the individual agents. This collective intelligence, referred to as swarm intelligence, is displayed in ant colonies when ants build elaborate nests, regulate nest temperature and efficiently search for food in very complex environments. In this thesis a proposal is made to utilize swarm intelligence to build a swarm automatic frequency planner (swarm AFP). The swarm AFP produces frequency plans that are better, or on par with existing frequency planning tools, and in a fraction of the time. A swarm AFP is presented through an in-depth investigation into complex adaptive systems, agent architectures and emergence. Based on an understanding of these concepts, a swarm intelligence model called ACEUS is constructed. ACEUS forms the platform of the swarm AFP. It is a contribution to multi-agent technology as it is a new multi-agent framework that exhibits swarm intelligence and complex distributed computation. What differentiates ACEUS from other multi-agent technologies is that ACEUS works on the basis that the tasks or constructions that have been created by the agents actually guide the agents in their endeavours. There is no centralised agent controlling or guiding the process. The agents in ACEUS receive information and stimulation from their tasks or constructions in the environment. As these constructions or tasks alter the environment, the agents receive stimulus from the changing environment and then react to the changing environment. The changing environment acts as an emergent guiding force to the agents. This is the important contribution that stigmergy contributes to ACEUS. Utilizing this concept, ACEUS is used to create a swarm AFP. The swarm AFP is benchmarked against the COST 259 Siemens benchmarks. In all the COST 259 Siemens scenarios the swarm AFP produced the best results in the shortest time. The swarm AFP was also tested in a real cellular network and the resulting statistics before and after the swarm AFP implementation are presented.

As bandwidth constraints on LAN/WAN environments decrease, the demand for distributed services will continue to increase. In particular, the proliferation of user-level applications requiring high-capacity distributed file storage systems will demand that such services be universally available. At the same time, the advent of high-speed networks have made the deployment of application and communication solutions based upon an Intelligent Mobile Agent (IMA) framework practical. Agents have proven to present an ideal development paradigm for the creation of autonomous large-scale distributed systems, and an agent-based communication scheme would facilitate the creation of independently administered distributed file services. This thesis thus outlines an architecture for such a distributed file system based upon an IMA communication framework.

This thesis deals with agent behavior evolution for the environment of a real computer game using evolutionary algorithms. The game Unreal Tournament 2004 was chosen, due to its ease of use for creating agents manually with the Pogamut suite of tools. As a decision making structure for the agents yaPOSH reactive plans were used. Due to the demanding needs on the hardware and time a real computer game is not considered to be very suitable for artificial evolution. To overcome this fact a light-weighted environment LightEnv, that simulates only those aspects that are important for agent evolution, was created. The evolution was based on genetic programming modified for use with yaPOSH reactive plans. The evolved agent behavior for death match and team death match game scenarios exceeded the preprogrammed ones and was successfully transferred to Unreal Tournament 2004 environment. In the team death match scenario an interesting behavior that utilizes agent communication was evolved.

Recent technological advances have witnessed the rapid encroachment of computing systems into our social spaces. Their acceptance in these social spaces by other occupants, however, might be mostly contingent on their social appropriateness. Notions of social appropriateness might seem vague but even people who don’t act on this commonsense knowledge, and accord to social norms, can sometimes find themselves ostracized from society. It is reflected in behavior that supports a sense of successful engagement and connection. Such behavior communicates a desire to be accepted and a willingness to engage, as opposed to inappropriateness that conveys indifference, rejection or even danger. As social actors, how can systems improve their interactions with us in order to better succeed at their tasks? Perhaps, more interestingly, how might they even improve our communications with each other? In this thesis we describe a framework to identify opportunities to design systems that can begin to act appropriately in social settings, which we call Considerate Systems. It includes a design process and guidelines, which allows an interaction to be viewed from the perspectives of the user, system and task. It also includes an architecture that guides the addition of productive social responses to interactive systems. We demonstrate the utility of this framework by exploring two types of scenarios that impact social interactions in contrasting ways. Remote interactions (such as on a conference call) suffer from an impinging of social cues that people rely on while communicating. On the other hand, situated multitasking interactions (such as texting while driving) can easily overwhelm users and detract from their performance. The framework is applied towards the design of autonomous agents tackling problems endemic to such scenarios. We evaluate their success with respect to specific scenario goals. We conclude by noting that while the challenges of instilling computing systems with a sense of appropriateness seem daunting, our productive use of systems can be enhanced with them.

In this study, the researcher created a model and software application for identifying the factors that are relevant in the decision making process to select and implement Open-source applications in higher education. Open-source applications provide the programming syntax to the user for customization. Unlike proprietary software, where the source code is unavailable and illegal to alter, an Open-Source Software (OSS) application authorizes the user to edit and recompile the application to meet the specific needs of the institution or organization. OSS applications are either free or purchasable for a one-time fee. The rising cost of proprietary software has motivated many academic institutions to consider implementing OSS. Many IT professionals are investigating the advantages and disadvantages of open-source applications in an attempt to mitigate expensive yearly fees, licensures and maintenance costs required by proprietary software vendors. The data collected in the study represented OSS and non-OSS enabled institutions that were members of the Council of Higher Education and Accreditation (CHEA) Organization. Of the data collected from the institutions, a portion of the information was set aside for validation purposes. The model created in this research addressed the OSS concerns in higher education by identifying the experiences, institutional characteristics, and technical systems relevant to the selection and implementation of OSS applications. The researcher used the Visual Basic .NET programming language to create the model and software application that provided academic institutions with technical OSS information and support. The Intelligent Software Agent (ISA) simplified the data analysis process by providing a Graphical User Interface (GUI) for the user to enter and receive data. The results of this research allowed institutions to specify certain criteria such as highest degree awarded, relevant characteristics, and technological factors and then receive implementation suggestions for adopting OSS applications. The validation process indicated that the tabled data in the model and generated suggestions of the ISA were statistically comparable with the data that was set-aside for validation purposes.

Uma das principais motivações da Inteligência Artificial no contexto dos sistemas de entretenimento digital é criar personagens adaptáveis a novas situações, pouco previsíveis, com aprendizado rápido, memória de situações passadas e uma grande diversidade de comportamentos consistente e convincente ao longo do tempo. De acordo com recentes estudos desenvolvidos nos campos da Neurociência e da Psicologia, a capacidade de resolução de problemas não está unicamente atrelada à facilidade na manipulação de símbolos, mas também à exploração das características do ambiente e à interação social, que pode ser expressa na forma de fenômenos emocionais. Os resultados desses estudos confirmam o papel fundamental que cumprem a personalidade e as emoções nas atividades de percepção, planejamento, raciocínio, criatividade, aprendizagem, memória e tomada de decisão. Quando módulos para a manipulação de personalidade e emoções são incorporados à teoria de agentes, é possível a construção de Agentes com Comportamento Convincente (Believable Agents). O objetivo principal deste trabalho é desenvolver e implementar uma arquitetura de agentes inteligentes para construir personagens sintéticos cujos estados afetivos influenciam em suas atividades cognitivas. Para o desenvolvimento de tal arquitetura utilizou-se o modelo BDI (Beliefs, Desires e Intentions) como base e aos módulos existentes em uma implementação desse modelo foi incluído um Módulo Afetivo. Esse Módulo Afetivo é constituído por três submódulos (Personalidade, Humor e Emoção) e deve impactar nas atividades cognitivas de percepção, memória e tomada de decisão do agente. Duas provas de conceito (experimentos) foram construídas : a simulação do problema do ``Dilema do Prisioneiro Iterado\'\' e a versão computadorizada do ``Jogo da Memória\'\'. A construção desses experimentos permitiu avaliar empiricamente a influência da personalidade, humor e emoção nas atividades cognitivas dos agentes, e consequentemente no seu comportamento. Os resultados evidenciam que a utilização da nova arquitetura permite a construção de agentes com comportamentos mais coerentes, adaptativos e cooperativos quando comparados aos de agentes construídos com arquiteturas cujas atividades cognitivas não consideram o estado afetivo, e também produz um comportamento mais próximo de um agente humano que de um comportamento ótimo ou aleatório. Essa evidência de sucesso, apresentada nos resultados, mostra que os agentes construídos com a arquitetura proposta nessa dissertação indicam um avanço na direção do desenvolvimento dos Agentes com Comportamento Convincente. / One of the main motivations of Artificial Intelligence in the context of the digital entertainment systems is to create characters that are adaptable to new situations, unpredictable, fast learners, enable with memory of past situations and a variety of consistent and convincing behavior over time. According to recent studies conducted in the fields of Neuroscience and Psychology, the ability to solve problems is not only related to the capacity to manipulate symbols, but also to the ability to explore the environment and to engage into social interaction, which can be expressed as emotional phenomena. The results of these studies confirm the key role the personality and emotions play in the activities of perception, attention, planning, reasoning, creativity, learning, memory and decision making. When modules for handling personality and emotion, are incorporated in a theory of agents, it is possible to build Believable Agents. The main objective of this work is to develop and implement an intelligent agent architecture to build synthetic characters whose affective states influence their cognitive activities. To develop such architecture the BDI model (Beliefs, Desires and Intentions) was used as a basis, to which an Affective Module was included. The Affective Module consists of three sub-modules (Personality, Mood and Emotion), which influence the cognitive activities of perception, memory and decision making. Finally, two proofs of concept were built: the simulation of the problem of ``Iterated Prisoner\'s Dilemma\'\' and the computerized version of the ``Memory Game.\'\' The construction of these experiments allowed to evaluate empirically the influence of personality, mood and emotion in cognitive activities of agents and consequently in their behavior. The results show that using the proposed architecture one can build agents with more consistent, adaptive and cooperative behaviors when compared to agents built with architectures whose affective states do not influence their cognitive activities. It also produces a behavior that is closer to a human user than that of optimal or random behavior. This evidence of success, presented in the obtained results, show that agents built with the proposed architecture indicate an advance towards the development of Believable Agents.