Minimal Definition Signatures: Computation and Application to Ontology Alignment

In computer science, ontologies define a domain to facilitate knowledge representation and sharing, in a machine processable way. Ontologies approximate an actual world representation, and thus ontologies will differ for many reasons. Therefore knowledge sharing, and in general semantic interoperability, is inherently hindered or even precluded between heterogenous ontologies. Ontology matching addresses this fundamental issue by producing alignments, i.e. sets of correspondences that describe relations between semantically related entities of different ontologies. However, alignments are typically incomplete. In order to support and improve ontology alignment, and semantic interoperability in general, this thesis exploits the notion of implicit definability. Implicit definability is a semantic property of ontologies, signatures, and concepts (and roles) stating that whenever the signature is fixed under a given ontology then the definition of a particular concept (or role) is also fixed. This thesis introduces the notion of minimal definition signature (MDS) from which a given entity is implicitly definable, and presents a novel approach that provides an efficient way to compute in practice all MDSs of the definable entities. Furthermore, it investigates the application of MDSs in the context of alignment generation, evaluation, and negotiation (whereby agents cooperatively establish a mutually acceptable alignment to support opportunistic communication within open environments). As implicit definability permits defined entities to be removed without semantic loss, this thesis argues, that if the meaning of the defined entity is wholly fixed by the terms of its definition, only the terms in the definition are required to be mapped in order to map the defined entity itself; thus implicit definability entails a new type of definability-based correspondence correspondence. Therefore this thesis defines and explores the properties of definability- based correspondences, and extends several ontology alignment evaluation metrics in order to accommodate their assessment. As task signature coverage is a prerequisite of many knowledge-based tasks (e.g. service invocation), a definability-based, efficient approximation approach to obtaining minimal signature cover sets is presented. Moreover, this thesis outlines a specific alignment negotiation approach and shows that by considering definability, agents are better equipped to: (i) determine whether an alignment provides the necessary coverage to achieve a particular task (align the whole ontology, formulate a message or query); (ii) adhere to privacy and confidentiality constraints; and (iii) minimalise the cardinality of the resulting mutual alignment

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