Sociological Agents for Effective Social Action

This paper is concerned with the problem of how effective social interaction arises from individual social action and mind. The need to study the individual social mind, suggests a move towards the notion of sociological agents who can model their social environment as opposed to acting socially within it. This does not constrain such social behaviour; on the contrary, we argue that it provides the requisite information and understanding for such behaviour to be effective. We argue that effective social agents must be sociological in modelling agents and agent relationships. In this paper, we show how an existing agent framework leads naturally to the enumeration of a map of inter-agent relationships that can be modelled and exploited by sociological agents to enable more effective operation.

Modelling the Provenance of Data in Autonomous Systems

Determining the provenance of data, i.e. the process that led to that data, is vital in many disciplines. For example, in science, the process that produced a given result must be demonstrably rigorous for the result to be deemed reliable. A provenance system supports applications in recording adequate documentation about process executions to answer queries regarding provenance, and provides functionality to perform those queries. Several provenance systems are being developed, but all focus on systems in which the components are textitreactive, for example Web Services that act on the basis of a request, job submission system, etc. This limitation means that questions regarding the motives of autonomous actors, or textitagents, in such systems remain unanswerable in the general case. Such questions include: who was ultimately responsible for a given effect, what was their reason for initiating the process and does the effect of a process match what was intended to occur by those initiating the process? In this paper, we address this limitation by integrating two solutions: a generic, re-usable framework for representing the provenance of data in service-oriented architectures and a model for describing the goal-oriented delegation and engagement of agents in multi-agent systems. Using these solutions, we present algorithms to answer common questions regarding responsibility and success of a process and evaluate the approach with a simulated healthcare example.