Description: Intelligent real-time decision-making / support systems are intended to assist the decision-maker in managing complex objects and processes of different nature, subject to significant time constraints. Implementation of decision-making / decision support systems in full is possible only with the use of modern technologies of designing intellectual systems based on the concepts of distributed artificial intelligence, multiagency, dynamic knowledge bases, neural networks, cloud computing. Multiagent systems have great theoretical and practical potential to create intelligent agents, including the creating of reactive behavior models based on planning. The tasks of planning the behavior of agents in a decision-making / support systems environment which is characterized by high dynamism require particular flexibility in the methods of the intellectual agent. In such systems it is impossible or not enough to find a static plan, it is necessary to carry out a dynamic adaptation of some initial plan to the dynamic environment and, perhaps, a dynamic goal directly upon receipt of new information, that is, the development of methods specified in the section of methods lies in the plane of construction of methods of dynamic and adaptive planning. The article is given research into generalizing methods for solving agent behavior planning problems in intelligent decision support systems. The current state of the methods in the field of multiagent systems is investigated, and a number of topical tasks were highlighted, which require further research, which include: development of models of self-learning agents, development of methods of collective learning, development of methods of fuzzy inference in models of communication and behavior of agents.
Keywords: intelligent decision-making systems, decision support, multi-agent systems, agents in intelligent decision support systems, planning
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