Abstract
The article offers the results of a study of various multiagent systems on the example of a number of models and multiagent implementations for risk assessment with fuzzy initial information. General construction methods and issues are related to their behavior, criteria for the quality of system performance that highlighted. The regularities, interrelations between the properties and parameters used when specifying a multi-agent intelligent system are defined. Developed approaches for processing complexly structured information. Algorithms for constructing a multi-agent intelligent risk assessment system have been developed.
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