The effective use of the territories’ resource potential is of great importance in the present day conditions of wide technological capabilities. Being able to restore, forest resources serve important economic, environmental and social functions. This defines the complicated mechanisms of the territorial forest complex functioning, managing which requires providing for such conditions when the current and future needs of all interested parties would be met to the fullest extent possible. In this regard, the use of adequate predictive models of forestry development are of particular relevance. The main aim of the research with its findings presented in the article is the definition of common approaches to the creation of agent-based models of the regional forest complex allowing to assess the need and extent of various control actions for their optimal combinations and achieve the target functions when managing the regional forest complex. The authors used the methods of system approach, analysis and synthesis, generalization and comparison, classification and systematization. The research findings are: evaluation criteria of priority management goals of the regional forest complex for use in agent-based models; a method of constructing models of complex subject areas supporting the creation of agent-based models of regional forest complex; practical implementation of a real system agent-based model using the developed approaches. The article deals with the requirements to agent-based models of complex subject areas, evaluation criteria of the effectiveness of regional forest complex and the mechanisms of forest complex management at the regional level, a method of designing an agent-based model of the regional forest complex is given, an agent-based model of reforestation in the territory of the Sokolskiy municipal district, the Vologda Oblast is the presented. Currently the authors are working on the creation of complex agent-based models of the Vologda Oblast forest industry
Keywords
reforestation, forest complex, agent-based modeling