System modeling of agent interactions in multi-component labor environments of the construction industry

Abstract

Complex labor environments in the construction industry are characterized by a multi-level structure, a significant number of interrelated participants, and the dynamic nature of processes occurring within project implementation. The efficiency of such environments largely depends on the quality of interaction organization among individual system elements, including executors, managerial staff, contractors, and other stakeholders. At the same time, each participant operates according to their own objectives, resource constraints, and behavioral strategies, which complicates coordination and decision-making processes.

The application of a systems approach combined with agent-based modeling makes it possible to reflect the internal logic of such environments, taking into account the individual characteristics of actors and their interdependencies. An agent, as a model element, is interpreted as an autonomous unit capable of decision-making, adaptation to changes, and interaction with other agents within defined rules. Model development is based on describing the structure of the environment, defining agent types, their properties, and behavioral scenarios.

Of particular importance is the ability to reproduce processes of work coordination, resource allocation, and responses to external and internal disturbances. Simulation experiments enable the evaluation of the consequences of various managerial decisions and allow the identification of the most effective configurations of interactions. This creates the preconditions for reducing risks associated with uncertainty and improving the coherence of actions among participants in the construction process.

An additional important aspect is the integration of agent-based modeling with digital construction management technologies, particularly Building Information Modeling (BIM), monitoring systems, and data analytics tools. This integration enhances model accuracy, ensures real-time updating, and forms a foundation for supporting managerial decision-making throughout all stages of the facility life cycle. In the context of the industry’s digital transformation, agent-based models serve as an effective tool for predicting the behavior of complex systems, evaluating development scenarios, and optimizing interactions among participants.

The use of a systemic agent-based approach facilitates the formalization not only of technical and economic aspects but also of organizational and behavioral dimensions of activity, including communication processes, conflicts of interest, and levels of cooperation. This provides a deeper understanding of the functioning of multicomponent labor environments and creates a methodological basis for developing adaptive management mechanisms aimed at improving the efficiency of construction project implementation.