Resumen
The subject of the study is intellectual means in the system of managing an intelligent manufacturing agent; the goal is to ensure the quality of managing a flexible integrated robotic system by developing the intellectual decision support system. The following problems are solved in the work: current tendencies of developing and implementing the intelligent systems for production management are considered; the demands for developing simulation models of decision support systems for solving flexible integrated production systems are formulated; the logical model of a decision support system for an intelligent manufacturing agent is developed, this model describes the decision-making process in the form of the functioning strategy formation on the basis of the knowledge of the current state of the integrated system, the system of knowledge describing probable actions of the robotic equipment, the objectives of the production system, and adapts the strategy if the working space of the integrated system or its individual goals change; the system of knowledge of a flexible integrated system is presented as a set of standard description of probable actions for robotic equipment; the distributed workspace of integrated systems is considered and described; separate objects are identified using the means of computer vision. The research is based on the following theoretical and practical foundations: the theory of sets is used to represent general simulation models of the decision support system; the theory of predicates is used to create a logical model of decision-making; knowledge-oriented methods and the tools of Prolog programming language use used to represent the knowledge system of a flexible integrated system, the MatLab system is used to analyse the workspace of a flexible integrated system. The following results are obtained ? mathematical and informational software of the system for managing an intelligent production robotic agent is developed. The possibilities of the proposed model application in the system of managing an intelligent robot are shown and the ways for improving such systems are suggested.