Thesis (Ph. D.)--University of Texas at Austin, 2003. / Supervisor: Joydeep Ghosh. Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 189-197). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph.D) - University of Karlsruhe, 2001. / Includes bibliographical references and index. Also available via the World Wide Web.

Thesis (M.S. in Computer Science)--Naval Postgraduate School, March 2003. / Thesis advisor(s): Neil C. Rowe. Includes bibliographical references (p. 65-67). Also available online.

published_or_final_version / Mechanical Engineering / Doctoral / Doctor of Philosophy

Not available / text

The concept of trust in multi-agent systems (MASs) has received significant attention in recent years, and a number of approaches have been proposed to enable agents to form, maintain and use trust relationships in their dealings with others.  However, current approaches do not adequately address <i>highly dynamic </i>multi-agent systems, where the population and structure changes frequently.  For example, agents may frequently join and leave, and ad-hoc structures may form in response to emerging situations. In these highly unstable environments, trust can be difficult or impossible to build with existing techniques.  Trust matters most when risk is involved, but in situations of extreme uncertainty, the risk may be too great to permit any interactions, resulting in a breakdown of the system. In this thesis, we propose a general approach for trust evaluation and decision-making in highly dynamic multi-agent systems.  First, we present a model of <i>stereotypes, </i>which allows agents to build tentative trust relationships with others on the basis of visible features.  We show that this approach can help agents to form trust relationships, despite a high degree of social dynamicity.  We present a method of selecting providers of trust evidence, when those providers may be stereotypically biased. Secondly, we present a trust decision-making model which employs <i>controls</i>, as well as trust evaluations and stereotypes, in order to facilitate initial interactions when trust is low or absent, and bootstrap dynamic societies.  We show that control can be used initially to enable interactions.  As trust builds, control can be reduced.  Our approach is general and applicable to existing models of trust in MASs.  We evaluate our model within a simulated multi-agent environment characterised by high degrees of dynamicity and structural change.

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Providing a logical characterisation of rational agent reasoning has been a long standing challenge in artificial intelligence (AI) research. It is a challenge that is not only of interest for the construction of AI agents, but is of equal importance in the modelling of agent behaviour. The goal of this thesis is to contribute to the formalisation of agent reasoning by showing that the computational limitations of agents is a vital component of modelling rational behaviour. To achieve this aim, both motivational and formal aspects of resource-bounded agents are examined. It is a central argument of this thesis that accounting for computational limitations is critical to the success of agent reasoning, yet has received only limited attention from the broader research community. Consequently, an important contribution of this thesis is in its advancing of motivational arguments in support of the need to account for computational limitations in agent reasoning research. As a natural progression from the motivational arguments, the majority of this thesis is devoted to an examination of propositional approximate logics. These logics represent a step towards the development of resource-bounded agents, but are also applicable to other areas of automated reasoning. This thesis makes a number of contributions in mapping the space of approximate logics. In particular, it draws a connection between approximate logics and knowledge compilation, by developing an approximate knowledge compilation method based on Cadoli and Schaerf??s S-3 family of approximate logics. This method allows for the incremental compilation of a knowledge base, thus reducing the need for a costly recompilation process. Furthermore, each approximate compilation has well-defined logical properties due to its correspondence to a particular S-3 logic. Important contributions are also made in the examination of approximate logics for clausal reasoning. Clausal reasoning is of particular interest due to the efficiency of modern clausal satisfiability solvers and the related research into problem hardness. In particular, Finger's Logics of Limited Bivalence are shown to be applicable to clausal reasoning. This is subsequently shown to logically characterise the behaviour of the well-known DPLL algorithm for determining boolean satisfiability, when subjected to restricted branching.

???Agent-based systems are one of the most vibrant and important areas of research and development to have emerged in information technology in the 1990s??? (Luck et al. 2003). The use of agents as a metaphor for designing and constructing software systems represents an innovative movement in the field of software engineering: ???Agent- Oriented Software Engineering (AOSE)??? (Lind 2000; Luck et al. 2003). This research contributes to the evolution of AOSE by proposing a comprehensive ontology-based methodology for the analysis and design of Multi-Agent Systems (MAS). The methodology is named MOBMAS, which stands for ???Methodology for Ontology-Based MASs???. A major improvement of MOBMAS over the existing agentoriented MAS development methodologies is its explicit and extensive support for ontology-based MAS development. Ontologies have been widely acknowledged for their significant benefits to interoperability, reusability, MAS development activities (such as system analysis and agent knowledge modelling) and MAS operation (such as agent communication and reasoning). Recognising these desirable ontology???s benefits, MOBMAS endeavours to identify and implement the various ways in which ontologies can be used in the MAS development process and integrated into the MAS model definitions. In so doing, MOBMAS has exploited ontologies to enhance its MAS development process and MAS development product with various strengths. These strengths include those ontology???s benefits listed above, and those additional benefits uncovered by MOBMAS, e.g. support for verification and validation, extendibility, maintainability and reliability. Compared to the numerous existing agent-oriented methodologies, MOBMAS is the first that explicitly and extensively investigates the diverse potential advantages of ontologies in MAS development, and which is able to implement these potential advantages via an ontology-based MAS development process and a set of ontology-based MAS model definitions. Another major contribution of MOBMAS to the field of AOSE is its ability to address all key concerns of MAS development in one methodological framework. The methodology provides support for a comprehensive list of methodological requirements, which are important to agent-oriented analysis and design, but which may not be wellsupported by the current methodologies. These methodological requirements were identified and validated by this research from three sources: the existing agent-oriented methodologies, the existing evaluation frameworks for agent-oriented methodologies and conventional system development methodologies, and a survey of practitioners and researchers in the field of AOSE. MOBMAS supports the identified methodological requirements by combining the strengths of the existing agent-oriented methodologies (i.e. by reusing and enhancing the various strong techniques and model definitions of the existing methodologies where appropriate), and by proposing new techniques and model definitions where necessary. The process of developing MOBMAS consisted of three sequential research activities. The first activity identified and validated a list of methodological requirements for an Agent Oriented Software Engineering methodology as mentioned above. The second research activity developed MOBMAS by specifying a development process, a set of techniques and a set of model definitions for supporting the identified methodological requirements. The final research activity evaluated and refined MOBMAS by collecting expert reviews on the methodology, using the methodology on an application and conducting a feature analysis of the methodology.