An architecture of multiple heterogeneous case-based reasoning employing agent technologies

This paper presents an investigation into applying Case-Based Reasoning to Multiple Heterogeneous Case Bases using agents. The adaptive CBR process and the architecture of the system are presented. A case study is presented to illustrate and evaluate the approach. The process of creating and maintaining the dynamic data structures is discussed. The similarity metrics employed by the system are used to support the process of optimisation of the collaboration between the agents which is based on the use of a blackboard architecture. The blackboard architecture is shown to support the efficient collaboration between the agents to achieve an efficient overall CBR solution, while using case-based reasoning methods to allow the overall system to adapt and “learn” new collaborative strategies for achieving the aims of the overall CBR problem solving process.

'Re-using an existing wheel' developing data architecture for cooperating autonomous and semi-autonomous, agent-based web services

This short position paper considers issues in developing Data Architecture for the Internet of Things (IoT) through the medium of an exemplar project, Domain Expertise Capture in Authoring and Development ­Environments (DECADE). A brief discussion sets the background for IoT, and the development of the ­distinction between things and computers. The paper makes a strong argument to avoid reinvention of the wheel, and to reuse approaches to distributed heterogeneous data architectures and the lessons learned from that work, and apply them to this situation. DECADE requires an autonomous recording system, ­local data storage, semi-autonomous verification model, sign-off mechanism, qualitative and ­quantitative ­analysis ­carried out when and where required through web-service architecture, based on ontology and analytic agents, with a self-maintaining ontology model. To develop this, we describe a web-service ­architecture, ­combining a distributed data warehouse, web services for analysis agents, ontology agents and a ­verification engine, with a centrally verified outcome database maintained by certifying body for qualification/­professional status.