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The paper describes the current state of agent-based modeling of geographical space and spatial economic systems. We explore reasons why this approach to modeling spatial phenomena is of particular interest. Agent-based models (ABMs) allow accounting for agents' spatial heterogeneity, the existing structure of the space, locality of interactions between agents. A survey of approaches to introducing space into the models and examples of the existing spatial models is presented. There is a great variety of spatial ABMs, but they relate predominantly to the local and city level, rather than to the economy as a whole. Spatial ABMs at the level of large regions and countries are not yet sufficiently developed, but have good prospects in the future. With increasing availability of geodata and technological development in general the number of applications and coverage of spatial ABM will grow

The significant progress observed in the field of artificial economy opens up new possibilities for modeling economic growth. Agent-based models (ABM) allow leaving the concept of a representative agent in the past and linking investment decisions of economic agents at the micro level with long-term macroeconomic growth. Modern ABMs offer new algorithms for modeling expectations, agent interaction, technical progress, pricing, and production planning. Our article analyzes the current state of modeling investment in fixed assets in operating macroeconomic ABMs. The subject of the review is the families of models Eurace, CATS, KS, Jamel, Lagom. The authors also present the investment block of the agent-based multiregional input-output model (ABMIOM) being developed. Comparative analysis demonstrates that modern ABMs, as a rule, implement the principle of stock-flow consistency. Modeling the investment process requires detailing the commodity nomenclature, so that the initially adopted two-sector division into investment and consumer goods is replaced by more detailed structures, which gives rise to the problem of accounting for inter-sectoral relations in production and consumption. The Leontief production function copes with this problem, which is confirmed by its widespread use in ABM. The size of firms' investments is often derived from the need to expand capacity in accordance with the current production plan, so that planning turns out to be myopic, and long-term aspects in ABM are still largely unrealized. Nevertheless, already now ABMs reproduce many phenomena associated with the economic cycle. The developed ABMIOM provides horizontal consistency of cash flows between agents and analysis of results using input-output tables. ABMIOM represents a step forward in reflecting intersectoral and interregional flows. The model reproduces the growth and contraction of the economy as a result of independent investment decisions of individual firms and households, which is reflected in the sectoral and spatial structure of the economy. Further development of ABMIOM is associated with the modeling of savings, intrafirm finance, money market, innovation and technical progress.