Provenance in Agent-mediated Healthcare Systems

Agent-oriented cooperation techniques and standardized electronic healthcare record exchange protocols can be used to combine information regarding different facets of a therapy received by a patient from different healthcare providers at different locations. Provenance is an innovative approach to trace events in complex distributed processes, dependencies between such events, and associated decisions by human actors. We focus on three aspects of provenance in agent-mediated healthcare systems: first, we define the provenance concept and show how it can be applied to agent-mediated healthcare applications; second, we investigate and provide a method for independent and autonomous healthcare agents to document the processes they are involved in without directly interacting with each other; and third, we show that this method solves the privacy issues of provenance in agent-mediated healthcare systems.

Extending Agent Languages for Autonomy

BDI agent languages provide a useful abstraction for complex systems comprised of interactive autonomous entities, but they have been used mostly in the context of single agents with a static plan library of behaviours invoked reactively. These languages provide a theoretically sound basis for agent design but are very limited in providing direct support for autonomy and societal cooperation needed for large scale systems. Some techniques for autonomy and cooperation have been explored in the past in ad hoc implementations, but not incorporated in any agent language. In order to address these shortcomings we extend the well known AgentSpeak(L) BDI agent language to include behaviour generation through planning, declarative goals and motivated goal adoption. We also develop a language-specific multiagent cooperation scheme and, to address potential problems arising from autonomy in a multiagent system, we extend our agents with a mechanism for norm processing leveraging existing theoretical work. These extensions allow for greater autonomy in the resulting systems, enabling them to synthesise new behaviours at runtime and to cooperate in non-scripted patterns.