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Shadowboard: an agent architecture for enacting a sophisticated digital self

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.

Identiferoai:union.ndltd.org:ADTP/245397
CreatorsGoschnick, Steven Brady
Source SetsAustraliasian Digital Theses Program
LanguageEnglish
Detected LanguageEnglish
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