Planning polyphase behavior of autonomous intelligent mobile systems in uncertain environments

Introduction: We discuss the modern ways of developing intelligent problem solvers, focusing on their shortcomings in terms efficiency application for planning purposeful behavior autonomous mobile systems a priori undescribed conditions environment. Purpose: Developing model knowledge representation and processing which would provide to organize activity uncertain Methods: Synthesis frame-like scenarios form polyvariable conditionally dependent predicates whose structure includes complex variables as well related types “object”, “event” “relationship”; synthesis heuristic rules process planning. In order represent predicates, fuzzy semantic networks are used can variously purposed without regard particular domains, being adaptable operational conditions. Results: have proposed various predicates. On base, an system activities unstable environments. Specially developed tools allow such automatically plan its space subtasks during fulfilment tasks formulated it. Practical relevance: The obtained results be efficiently building solvers purpose, capable performing