Reflective knowledge models to support an advanced HCI for decision management

Abstract In the previous years, the evolution of the telematics technology has introduced a new scenario of human–computer operation where the achievement of an adequate level of user–system interaction has become a key aspect. This issue is specially relevant in real-time management scenarios where the system is intended to provide an intelligent support to human operators in the decision-making task. This paper proposes the use of advanced knowledge-based models to support human–computer interaction in the context of real-time decision for management problems. The approach is mainly based on endowing intelligent systems with an introspection capability that makes possible an adaptive performance to the characteristics of the interaction. This capability is supported by a reflective architecture where a metalevel layer dynamically configures reasoning strategies to generate the required answers by looking into a structured collection of problem-solving components. The approach was developed and applied within the FLUIDS project, an European Commission Telematics Applications research project. The proposal is illustrated with an example in the domain of real-time private traffic management in the city of Turin.