Yu. I. Nechaev - Dr.Sc. (Eng.), Professor, Honored Scientist of RF, Academician of RANS, Leading Research Scientist, the main scientific employee of scientific research Institute of the high technology computer technologies of the St.-Petersburg National Research University Information Technologies, Mechanics and Optics. International expert in the field of high-performance computing and intelligence systems.

The problem of multiagent modeling on a basis neural-dynamic systems (ND-systems) is considered. Functioning of systems is carried out in the conditions of uncertainty at the analysis and the forecast of extreme situations. Interpretation of dynamics of interaction is based on use of achievements of the modern of catastrophe theory in the multiprocessor computing environment. Synthesis of multiagent managements is carried out in frameworks нейродинамической systems (ND-systems). Realization of management and interpretation of processes of interaction is conducted with the help neural-fuzzy and neural-evolution modeling. The system concept multiagent modeling allows to realize information processing in a mode of real time. The formal model of topological dynamics multiagent modeling provides use of fractal geometry and entropy the approach. Multiagent modeling is considered with reference to sea dynamic objects (DO) at various level of external indignations. The structure multiagent modeling within the limits of a paradigm of emergency calculations, and also extreme situations is considered at an estimation of behavior of a vessel on waves. The basic attention is given to the analysis multiagent modeling at realization of the active dynamic systems functioning on a basis og ND-system in the conditions of uncertainty and incompleteness of the initial information. Problems of modeling of behavior and training are considered with reference to dynamics interpretation multiagent systems. The practical application of the developed concept is discussed with reference to problems of interpretation of interaction of investigated non-stationary object with an environment in the DO of system evolution. The dynamic model of accidents defines system movement to target attractor and stability loss.

 

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