Identification of complex systems through reduced paths using the Spiral Discovery Method

Control theories of cognitive systems are gaining relevance as a result of two driving forces: the desire to create artificial cognitive systems, and the desire to influence or control biological ones. This paper introduces the Spiral Discovery Method (SDM) in a new context, with the goal of facilitating reduced path parameter identification of black-box systems. The approach appeals to human cognitive capabilities in that it reduces the number of possible interaction parameters, and in that it introduces a cyclical structure to the search path which helps in reducing the cognitive load associated with the search process. The proposed approach is demonstrated through a rudimentary parameter identification scenario, and future directions are discussed.