Abstract:

Current trends in regional analyzes require highly demanding mathematical and statistical calculations. This fact is due to significant amount of data and classification of economic systems as „soft systems“. Due to the fact that in these systems there are a number of factors, the structure of which is not precisely defined, the data are vague and incomplete, it is necessary to look for more effective analytical tools. At present, the characteristic feature of regional analyzes is the prediction of sustainability (sustainable region, sustainable processes). One of the dominant sectors influencing sustainability is tourism, which significantly affects the values of economic, social or environmental factors. These effects are due to increased movements of subjects in space and the subsequent action of subjects in preferred destinations. Transfers to these destinations are conditioned by the values of the significance criteria, autonomous entities choose the destination according to preferences, i.e. the entities try to maximize the values of their preferences, especially the quality of life. (Xu, et al., 2020; McGrath, 2020). Grouping of subjects in destinations leads to a change of environment. Changes in the values of preference factors may occur. Autonomous entities will define new criteria for maximizing the values of their preferences, therefore it can be assumed that there will be a change in the significance of destinations and the transfer of entities to other destinations. As a progressive tool for mapping infrastructure and finding local extremes, which quantify the requirements of entities and serve to identify the movement of autonomous entities, at present, characterized by a high degree of use of ICT (Industry 4), artificial intelligence and autonomous systems based on a multiagent environment appear. According to (Reis, 2020), artificial intelligence (AI) is at the heart of academic and public debate and an important progressive tool. The authors conducted an extensive literature search and examined the impact of AI on European Union (EU) policy. Multiagent approaches to the analysis of sustainable development are presented, for example, by studies (Pons-Pons, et al., 2012), the authors present a georeferenced agent-based model.