In a groundbreaking study published in the *Collection of Papers New Economy* (translated as *Collection of Papers New Economy*), Yevgen Kotukh of the National Technical University “Dnipro Polytechnic” in Ukraine has introduced a novel approach to modeling budgeting processes in local communities, or *hromadas*. His research leverages multi-agent systems (MAS) to simulate economic interactions at the local level, offering a more dynamic and realistic framework for resource allocation and strategic planning.
Traditional budgeting models often rely on static assumptions, overlooking the complexities of human decision-making and the fluid nature of economic interactions. Kotukh’s work addresses these limitations by incorporating agent-oriented modeling, which accounts for heterogeneity, bounded rationality, and evolving relationships among economic actors. This approach allows for a more nuanced simulation of how local governments, businesses, and residents interact in budgetary processes.
At the core of Kotukh’s methodology is a budget auction model based on game theory. In this system, economic actors compete for resource distribution, with the auction mechanism identifying production functions and utility values for each participant. The model then iteratively optimizes resource allocation based on predefined efficiency criteria. This structured competition not only enhances transparency but also ensures that resources are allocated in a way that maximizes collective benefit.
“By integrating game theory with reinforcement learning, we can simulate how agents adapt their strategies over time,” Kotukh explains. “This iterative process allows for continuous improvement in decision-making, making the system more resilient and efficient.”
The proposed framework also incorporates reinforcement learning, specifically multi-agent reinforcement learning (MARL), where agents refine their strategies through interaction and feedback. This dynamic adaptation is crucial for addressing real-world challenges, such as resource allocation optimization and strategic planning for sustainable development.
Kotukh’s research is particularly relevant in the context of Ukraine’s decentralization reforms and post-war recovery efforts. By providing a tool for transparent, participatory, and efficiency-driven public finance management, his methodology could support the digital transformation of local governance. The model’s ability to align resource distribution with sustainable development goals makes it a valuable asset for policymakers and local administrators.
Beyond Ukraine, the implications of this research extend to other regions facing similar challenges. The MAS approach could be applied to various sectors, including energy, where decentralized decision-making and resource optimization are critical. For instance, local energy cooperatives could use this model to allocate funds for renewable energy projects, ensuring that investments align with community needs and long-term sustainability goals.
Kotukh’s work also highlights the potential for intelligent public finance systems. By integrating advanced computational techniques with traditional budgeting processes, local hromadas can achieve greater efficiency and accountability. This could lead to more effective crisis management, as well as enhanced resilience in the face of economic and environmental challenges.
As the energy sector increasingly embraces decentralized and community-driven models, Kotukh’s research offers a blueprint for leveraging technology to enhance decision-making. By fostering collaboration among local stakeholders, this approach could pave the way for more sustainable and equitable energy systems. The study’s publication in the *Collection of Papers New Economy* underscores its relevance to both academic and practical applications, positioning it as a key contribution to the field of public finance and local governance.
