Abstract

This paper describes an approach to the automatic generation of a mivar knowledge base of a three-dimensional logic space. This knowledge base is created to provide three-dimensional robot movement. Automatic generation of mivar knowledge bases is necessary for the further solution of the problem of planning three-dimensional routes of robots and robotic complexes. This work is the basis for solving problems of resource allocation optimization in the field of transport logistics and machine learning artificial intelligence based on the application of mivar technologies. The variant of practical realization of the automated technique of sequential removal of mivar network rules and search for new robot motion trajectories for their further comparison by the number of activated transition rules on the way from the initial location to the target one is considered. Mivar-based logic artificial intelligence technologies offer great opportunities for dynamic route finding in real time, which will help in further development of machine learning artificial intelligence in the field of transport systems. The paper is intended for researchers involved in the development of mivar expert systems for solving problems of three-dimensional movement of robots and optimizing production planning systems.

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