Inter-organizational Interoperability through integration of Multiagent, Web Service, and Semantic Web Technologies

This paper presents a software architecture for inter-organizational multiagent systems. The architecture integrates Web service technology into multiagent systems to overcome the technical interoperability problem of current multiagent systems in the fast growing service-oriented environments. We integrate Semantic Web technology to make multiagent systems semantically interoperable. We address the problem of interoperability regarding interfaces, messaging protocols, data exchanged, and security whilst considering a dynamic e-business environment. The proposed architecture enables service virtualization, secure service access across organizational boundaries, service-to-agent communication, and OWL reasoning within agents

Representação de dados semânticos em agentes BDI

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2014A crescente necessidade de informação e consequente aumento no volume de comunicação tem conduzido a adoção de dados semânticos e resultando numa demanda por ferramentas que manipulam tais dados. Com o avanço de dados semânticos na Web, estamos atingindo um ponto onde ferramentas de software devem se adaptar a este novo formato. Este trabalho propõe um novo modelo para desenvolvimento de agentes inteligentes da IA baseados em um modelo de logica BDI, com o objetivo de permitir comunicação livre de ambiguidade e capaz de reutilizar dados semânticos já existentes na Web. O modelo propõe uma alternativa para a representação de dados semânticos no agente, como estes dados podem ser armazenados e utilizados para comunicação com triplestores da Web Semântica e também com outros agentes (semânticos e não semânticos). Com foco na representação destes dados semânticos, são exploradas maneiras de se integrar informação semântica a um agente, seus processos e estados e porque esta integração pode levar a melhores resultados quando acessando informação na Web. Além disso, e demonstrado o ganho que se pode obter ao reutilizar dados já existentes na Web Semântica, e como isto pode facilitar o desenvolvimento de novas aplicações baseadas em agentes. Finalmente, para avaliar o modelo proposto, e feita uma comparação qualitativa com outros trabalhos na área, levantando as diferenças, motivações e melhorias feitas neste trabalho. Uma implementação deste modelo e apresentada através de um arcabouço criado para demonstrar e validar as intenções deste trabalho. Este arcabouço chamado PySA e descrito expondo os principais pontos defendidos na proposta, testando em situações hipotéticas e exemplos reais a comunicação e aprendizado semanticamente rico que são os objetivos do trabalho.Abstract: Increasing needs for information and consequent increase in communication volume are leading to a widespread adoption of semantic data and demand for tools that manipulate such data. With the uprising of Semantic Web data, we are reaching a point where software tools must adapt to this new format. This work proposes a new model for developing intelligent agents based on a BDI reasoning model, with the goal of allowing ambiguity free communication and capable of reusing semantic data that already exists in the Web. The model proposes an alternative to representing semantic data in agents, and how this data can be stored and utilized to communicate with Semantic Web stores and also other agents (semantic and non-semantic). Focusing on the representation of this semantic data, this work explores ways to integrate semantic information to an agent, it's processes and states and why this integration can lead to better results when acessing information in the Web. On top of that, this work demonstrates what gain can be obtained from reutilizing data that already exists in the Semantic Web, and how this eases the development of new agent-based applications.Finally, to evaluate the proposed model, a qualitative comparison is made with similar work in the area, comparing the dierences, motivations and improvements made in this project. An implementation of this model is presented through a framework created to demonstrate and validate in practice the intentions of this project. This framework called PySA is described, exposing the main values defended in the proposal, testing in hypothetical situations and real examples the semantically rich communication and learning capabilities that are the main goal of this work

Personality representation: predicting behaviour for personalised learning support

The need for personalised support systems comes from the growing number of students that are being supported within institutions with shrinking resources. Over the last decade the use of computers and the Internet within education has become more predominant. This opens up a range of possibilities in regard to spreading that resource further and more effectively. Previous attempts to create automated systems such as intelligent tutoring systems and learning companions have been criticised for being pedagogically ineffective and relying on large knowledge sources which restrict their domain of application. More recent work on adaptive hypermedia has resolved some of these issues but has been criticised for the lack of support scope, focusing on learning paths and alternative content presentation. The student model used within these systems is also of limited scope and often based on learning history or learning styles.This research examines the potential of using a personality theory as the basis for a personalisation mechanism within an educational support system. The automated support system is designed to utilise a personality based profile to predict student behaviour. This prediction is then used to select the most appropriate feedback from a selection of reflective hints for students performing lab based programming activities. The rationale for the use of personality is simply that this is the concept psychologists use for identifying individual differences and similarities which are expressed in everyday behaviour. Therefore the research has investigated how these characteristics can be modelled in order to provide a fundamental understanding of the student user and thus be able to provide tailored support. As personality is used to describe individuals across many situations and behaviours, the use of such at the core of a personalisation mechanism may overcome the issues of scope experienced by previous methods.This research poses the following question: can a representation of personality be used to predict behaviour within a software system, in such a way, as to be able to personalise support?Putting forward the central claim that it is feasible to capture and represent personality within a software system for the purpose of personalising services.The research uses a mixed methods approach including a number and combination of quantitative and qualitative methods for both investigation and determining the feasibility of this approach.The main contribution of the thesis has been the development of a set of profiling models from psychological theories, which account for both individual differences and group similarities, as a means of personalising services. These are then applied to the development of a prototype system which utilises a personality based profile. The evidence from the evaluation of the developed prototype system has demonstrated an ability to predict student behaviour with limited success and personalise support.The limitations of the evaluation study and implementation difficulties suggest that the approach taken in this research is not feasible. Further research and exploration is required –particularly in the application to a subject area outside that of programming

Ubiquitous Robotics System for Knowledge-based Auto-configuration System for Service Delivery within Smart Home Environments

The future smart home will be enhanced and driven by the recent advance of the Internet of Things (IoT), which advocates the integration of computational devices within an Internet architecture on a global scale [1, 2]. In the IoT paradigm, the smart home will be developed by interconnecting a plethora of smart objects both inside and outside the home environment [3-5]. The recent take-up of these connected devices within home environments is slowly and surely transforming traditional home living environments. Such connected and integrated home environments lead to the concept of the smart home, which has attracted significant research efforts to enhance the functionality of home environments with a wide range of novel services. The wide availability of services and devices within contemporary smart home environments make their management a challenging and rewarding task. The trend whereby the development of smart home services is decoupled from that of smart home devices increases the complexity of this task. As such, it is desirable that smart home services are developed and deployed independently, rather than pre-bundled with specific devices, although it must be recognised that this is not always practical. Moreover, systems need to facilitate the deployment process and cope with any changes in the target environment after deployment. Maintaining complex smart home systems throughout their lifecycle entails considerable resources and effort. These challenges have stimulated the need for dynamic auto-configurable services amongst such distributed systems. Although significant research has been directed towards achieving auto-configuration, none of the existing solutions is sufficient to achieve auto-configuration within smart home environments. All such solutions are considered incomplete, as they lack the ability to meet all smart home requirements efficiently. These requirements include the ability to adapt flexibly to new and dynamic home environments without direct user intervention. Fulfilling these requirements would enhance the performance of smart home systems and help to address cost-effectiveness, considering the financial implications of the manual configuration of smart home environments. Current configuration approaches fail to meet one or more of the requirements of smart homes. If one of these approaches meets the flexibility criterion, the configuration is either not executed online without affecting the system or requires direct user intervention. In other words, there is no adequate solution to allow smart home systems to adapt dynamically to changing circumstances, hence to enable the correct interconnections among its components without direct user intervention and the interruption of the whole system. Therefore, it is necessary to develop an efficient, adaptive, agile and flexible system that adapts dynamically to each new requirement of the smart home environment. This research aims to devise methods to automate the activities associated with customised service delivery for dynamic home environments by exploiting recent advances in the field of ubiquitous robotics and Semantic Web technologies. It introduces a novel approach called the Knowledge-based Auto-configuration Software Robot (Sobot) for Smart Home Environments, which utilises the Sobot to achieve auto-configuration of the system. The research work was conducted under the Distributed Integrated Care Services and Systems (iCARE) project, which was designed to accomplish and deliver integrated distributed ecosystems with a homecare focus. The auto-configuration Sobot which is the focus of this thesis is a key component of the iCARE project. It will become one of the key enabling technologies for generic smart home environments. It has a profound impact on designing and implementing a high quality system. Its main role is to generate a feasible configuration that meets the given requirements using the knowledgebase of the smart home environment as a core component. The knowledgebase plays a pivotal role in helping the Sobot to automatically select the most appropriate resources in a given context-aware system via semantic searching and matching. Ontology as a technique of knowledgebase representation generally helps to design and develop a specific domain. It is also a key technology for the Semantic Web, which enables a common understanding amongst software agents and people, clarifies the domain assumptions and facilitates the reuse and analysis of its knowledge. The main advantages of the Sobot over traditional applications is its awareness of the changing digital and physical environments and its ability to interpret these changes, extract the relevant contextual data and merge any new information or knowledge. The Sobot is capable of creating new or alternative feasible configurations to meet the system’s goal by utilising inferred facts based on the smart home ontological model, so that the system can adapt to the changed environment. Furthermore, the Sobot has the capability to execute the generated reconfiguration plan without interrupting the running of the system. A proof-of-concept testbed has been designed and implemented. The case studies carried out have shown the potential of the proposed approach to achieve flexible and reliable auto-configuration of the smart home system, with promising directions for future research

A requirements elicitation framework for agent-oriented software engineering.

The hypothesis of this research is as follows: "Conceptual modelling is a useful activity for the early part of gathering requirements for agent-based systems." This thesis examines the difficulties of gathering and expressing requirements for agent based systems, and describes the development of a requirements elicitation framework. Conceptual modelling in the form of Conceptual Graphs is offered as a means of representing the constituent parts of an agent-based system. In particular, use of a specific graph, the Transaction Model, illustrates how complex agent concepts can be modelled and tested prior to detailed design specification, by utilising a design metaphor for an organisational activity.Using an exemplar in the healthcare domain, a preliminary design framework is developed showing how the Transaction Agent Modelling (TrAM) approach assisted the design of complex community healthcare payment models. Insight gained during the design process is used to enrich and refine the framework in order that detailed ontological specifications can be constructed, before validating with a mobile learning scenario. The ensuing discussion evaluates how useful the approach is, and demonstrates the following contributions: Use of the Transaction Model to impose a rigour upon the requirements elicitation process for agent-based systems; Use of Conceptual Graph type hierarchies for ontology construction; A means to check the transaction models using graphical inferencing with Peirce Logic; Provision of a method for the elicitation and decomposition of soft goals; The TrAM process for agent system requirements elicitation

Toward Shared Understanding : An Argumentation Based Approach for Communication in Open Multi-Agent Systems

Open distributed computing applications are becoming increasingly commonplace nowadays. In many cases, these applications are composed of multiple autonomous agents, each with its own aims and objectives. In such complex systems, communication between these agents is usually essential for them to perform their task, to coordinate their actions and share their knowledge. However, successful and meaningful communication can only be achieved by a shared understanding of each other's messages. Therefore efficient mechanisms are needed to reach a mutual understanding when exchanging expressions from each other's world model and background knowledge. We believe the de facto mechanisms for achieving this are ontologies, and this is the area explored in this thesis [88]. However, supporting shared understanding mechanisms for open distributed applications is a major research challenge. Specifically, one consequence of a system being open is the heterogeneity of the agents. Agents may have conflicting goals, or may be heterogeneous with respect to their beliefs or their knowledge. Forcing all agents to use a common vocabulary defined in one or more shared ontologies is, thus, an oversimplified solution, particularly when these agents are designed and deployed independently of each other. This thesis proposes a novel approach to overcome vocabulary heterogeneity, where the agents dynamically negotiate the meaning of the terms they use to communicate. While many proposals for aligning two agent ontologies have been presented in the literature as the current standard approaches to resolve heterogeneity, they are lacking when dealing with important features of agents and their environment. Motivated by the hypothesis that ontology alignment approaches should reflect the characteristics of autonomy and rationality that are typical of agents, and should also be tailored to the requirements of an open environment, such as dynamism, we propose a way for agents to define and agree upon the semantics of the terms used at run-time, according to their interests and preferences. Since agents are autonomous and represent different stakeholders, the process by which they come to an agreement will necessarily only come through negotiation. By using argumentation theory, agents generate and exchange different arguments, that support or reject possible mappings between vocabularies, according to their own preferences. Thus, this work provides a concrete instantiation of the meaning negotiation process that we would like agents to achieve, and that may lead to shared understanding. Moreover, in contrast to current ontology alignment approaches, the choice of a mapping is based on two clearly identified elements: (i) the argumentation framework, which is common to all agents, and (ii) the preference relations, which are private to each agent. Despite the large body of work in the area of semantic interoperabiJity, we are not aware of any research in this area that has directly addressed these important requirements for open Multi-Agent Systems as we have done in this thesis. Supplied by The British Library - 'The world's knowledge

Investigating communicating sequential processes for Java to support ubiquitous computing

Ubiquitous Computing promises to enrich our everyday lives by enabling the environment to be enhanced via computational elements. These elements are designed to augment and support our lives, thus allowing us to perform our tasks and goals. The main facet of Ubiquitous Computing is that computational devices are embedded in the environment, and interact with users and themselves to provide novel and unique applications. Ubiquitous Computing requires an underlying architecture that helps to promote and control the dynamic properties and structures that the applications require. In this thesis, the Networking package of Communicating Sequential Processes for Java (JCSP) is examined to analyse its suitability as the underlying architecture for Ubiquitous Computing. The reason to use JCSP Networking as a case study is that one of the proposed models for Ubiquitous Computing, the ?-Calculus, has the potential to have its abstractions implemented within JCSP Networking. This thesis examines some of the underlying properties of JCSP Networking and examines them within the context of Ubiquitous Computing. There is also an examination into the possibility of implementing the mobility constructs of the ?-Calculus and similar mobility models within JCSP Networking. It has been found that some of the inherent properties of Java and JCSP Networking do cause limitations, and hence a generalisation of the architecture has been made that should provide greater suitability of the ideas behind JCSP Networking to support Ubiquitous Computing. The generalisation has resulted in the creation of a verified communication protocol that can be applied to any Communicating Process Architecture