Architecture of the tool for developing the functional hybrid intelligent systems with a heterogeneous visual field

Hybrid intelligent systems integrating experts' knowledge models solve heterogeneous tasks (problems). At the same time, elements of hybrid intelligent systems interact using symbolic-logical models of knowledge, which significantly limit their capabilities in comparison with teams of experts who successfully argue both logically and figuratively. A typical architecture of hybrid intelligent systems that synthesize integrated methods for solving problems over a heterogeneous visual field and an architecture of the tool for developing such systems are proposed. Hybrid intelligent systems with a heterogeneous visual field alternately simulate collective verbal-symbolic and visual-figurative reasoning depending on the uncertainty of the decision-making situation. Visual-figurative reasoning allows the system to “see” an approximate solution of the problem which can be refined later by the methods of verbal-symbolic reasoning.