Computing and Information Systems - Theses

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End date: 2001 × Start date: 2001 × Type: Masters Research thesis ×

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    Shadowboard: an agent architecture for enacting a sophisticated digital self
    Goschnick, Steven Brady ( 2001-09)
    In recent years many people have built Personal Assistant Agents, Information Agents and the like, and have simply added them to the operating system as auxiliary applications, without regard to architecture. This thesis argues that an agent architecture, one designed as a sophisticated representation of an individual user, should be embedded deep in the device system software, with at least equal status to the GUI – the graphical user interface. A sophisticated model of the user is then built, drawing upon contemporary Analytical Psychology – the Psychology of Subselves. The Shadowboard Agent architecture is then built upon that user model, drawing both structural and computational implications from the underlying psychology. An XML DTD file named Shadowboard.dtd is declared as a practical manifestation of the semantics of Shadowboard. An implementation of the Shadowboard system is mapped out, via a planned conversion of two existing integrated systems: SlimWinX, an event-driven GUI system; and XSpaces, an object-oriented tuplespace system with Blackboard-like features. The decision making mechanism passes logic terms and contraints between the various sub-agent components (some of which take on the role of Constraint Solvers), giving this agent system some characteristics of a Generalised Constraint Solver. A Shadowboard agent (built using the system) consists of a central controlling autonomous agent named the Aware Ego Agent, and any number of sub-agents, which collectively form an integrated but singular whole agent modelled on the user called the Digital Self. One such whole-agent is defined in a file named DigitalSelf.xml – which conforms to the schema in Shadowboard.dtd - which offers a comprehensive and generic representation of a user’s stance in a 24x7 network, in particular - the Internet. Numerous types of Shadowboard sub-agents are declared.
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    Predicting the priority of email messages using stylistic features
    Ward, Belinda ( 2001)
    LASSIE (Learning Apprentice System for Sorting Incoming Email) is an email management tool that has been constructed in order to demonstrate a possible solution to the problem of email overload. It is designed to help users manage their incoming messages more efficiently by sorting the messages according to their level of urgency. This thesis discusses the motivation and requirements for such a system, and describes the design, implementation, and evaluation of LASSIE. We identify stylistic features that are good indicators of message urgency, describe how these features can be extracted from plain text messages, and present an algorithm for inferring the relationship between these attributes and the message urgency for any individual user. We discuss the considerations involved in constructing a practical email management tool and describe the design decisions that were made in constructing LASSIE. The results of a user trial indicate that LASSIE is able to achieve a high level of predictive accuracy and is readily adopted by users, although improvements in its long-term performance are desirable.