PyramidSim

PyramidSim is a Python-based simulation framework designed for modeling and analyzing complex systems, particularly those involving hierarchical structures such as organizations, biological networks, or computational architectures. Developed as an open-source tool, it provides a modular and flexible approach to simulating dynamic processes across multiple layers, making it useful for researchers and practitioners in fields like operations research, systems engineering, and social sciences.

The framework is built around a layered architecture, where each layer represents a different level of abstraction—such as individual agents, teams, departments, or entire organizations. Users can define rules and interactions at each level, allowing for detailed modeling of how decisions, behaviors, or resources propagate through the system. This hierarchical approach enables simulations to capture emergent phenomena, such as cascading effects or collective decision-making, without requiring excessive computational resources.

PyramidSim supports various simulation techniques, including discrete-event modeling and agent-based simulations, and integrates with libraries like NumPy and Pandas for data analysis. Its modular design allows users to extend functionality by adding custom modules or adapting existing ones to fit specific use cases. The framework also includes visualization tools to help interpret simulation results, such as network diagrams, time-series plots, and hierarchical tree structures.

While primarily used for academic and research purposes, PyramidSim has applications in strategic planning, risk assessment, and policy analysis. Its ease of use and adaptability make it accessible to both novices and experienced modelers, though familiarity with Python and simulation concepts is beneficial. The project maintains an active community, with documentation, tutorials, and example models available to assist new users in getting started.

PyramidSim continues to evolve through community contributions and collaborative development, aiming to provide a robust platform for exploring complex systems in a structured yet flexible manner.