Towards a Methodology for Coordination Mechanism Selection in Open Systems

Agent-oriented software engineering (AOSE) is a promising approach to developing applications for dynamic open systems. If well developed, these applications can be opportunistic, taking advantage of services implemented by other developers at appropriate times. However, methodologies are needed to aid the development of systems that are both flexible enough to be opportunistic and tightly defined by the application requirements. In this paper, we investigate how developers can choose the coordination mechanisms of agents so that the agents will best fulfil application requirements in an open system.

Extracting Causal Graphs from an Open Provenance Data Model

The open provenance architecture (OPA) approach to the challenge was distinct in several regards. In particular, it is based on an open, well-defined data model and architecture, allowing different components of the challenge workflow to independently record documentation, and for the workflow to be executed in any environment. Another noticeable feature is that we distinguish between the data recorded about what has occurred, emphprocess documentation, and the emphprovenance of a data item, which is all that caused the data item to be as it is and is obtained as the result of a query over process documentation. This distinction allows us to tailor the system to separately best address the requirements of recording and querying documentation. Other notable features include the explicit recording of causal relationships between both events and data items, an interaction-based world model, intensional definition of data items in queries rather than relying on explicit naming mechanisms, and emphstyling of documentation to support non-functional application requirements such as reducing storage costs or ensuring privacy of data. In this paper we describe how each of these features aid us in answering the challenge provenance queries.