DEVELOPMENT OF DISTRIBUTED PROBLEM-SOLVING SYSTEMS FOR DYNAMIC ENVIRONMENTS

As knowledge-based techniques are introduced in supervision and control applications, the need for a structured, methodological approach in the development of these systems increases. Current knowledge-based systems development methodologies are founded on individualistic models of expertise, and cannot face the challenge of interacting with humans or other systems in dynamic application environments. This article introduces a development method that combines models of expertise with interaction-based distributed artificial intelligence. The applicability of the method is demonstrated on an example of supervision of a power transmission network. The analysis of the proposed system is based on the KADS methodology. The design phase is structured in a series of steps: first, the domain description is used to select a model of distributed problem solving. Then, problem constraints and a set of design rules guide the mapping of the analysis' entities to a design solution. Design decisions are justified at every step. Alternative design proposals are experimentally compared with the aid of a multi-agent platform and a simulator. The experimental results indicate possible design refinements. Finally, the generality of the approach is discussed and future research directions are indicated.