The article examines virtual game spaces as research testbeds for evaluating hypotheses about the behavior of complex systems. Its relevance follows from the growing number of domains in which field observation is constrained by ethics, logistics, or limited parameter control, while modeling still demands empirical calibration. The contribution lies in an analytical account of game design as a research practice aligned with systems science: the designer constructs a parameterized environment, specifies rules, agent types, feedback channels, and observable metrics, then interprets resulting regimes as data suitable for refining assumptions. The paper outlines principles for staging “game experiments,” describes procedures for linking observed patterns to distributional models and dynamic processes, and explains how emergent effects arise and how they can be translated into testable statements. To achieve this aim, the study applies analysis of recent scholarship, comparison of methodological approaches, and conceptual modeling of the whole research cycle. The material is grounded in scientific publications from 2022 to –2025. The article targets researchers who use simulations, agent-based models, and game-derived methods in social, economic, and social-ecological problem settings.

virtual game spaces, game design as research, parameterized environments, experimental hypothesis testing, agent-based modeling, multi-agent learning, emergence, behavioral patterns, research games, complex systems

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