ABMia

ABMia is an open-source platform designed to support agent-based modeling and AI-driven simulation of complex adaptive systems. It provides a modeling language and runtime that allow researchers to define agents, environments, and interactions, and to integrate machine learning components for autonomous decision-making. The project emphasizes reproducibility, modularity, and collaboration, offering tooling for experiment management, data collection, and visualization.

History and development: ABMia emerged from a collaboration among universities and research labs in the early 2010s to bridge agent-based models with modern AI techniques. The first public release introduced a modular engine and a Python API. Since then the project has evolved through community contributions, ongoing maintenance by a core team, and regular releases that improve scalability, interoperability, and documentation.

Architecture and features: The core engine executes agent-based simulations with a flexible scheduler, supports parallel and distributed execution, and provides a library of reusable agent templates. It includes a domain-specific modeling language and APIs for Python and R, enabling integration with ML libraries. Built-in data collection, experiment tracking, and versioned scenarios help reproducibility. Visualization dashboards and export tools facilitate analysis and sharing of results.

Applications and reception: ABMia is used in social science research, epidemiology, traffic and urban planning, ecology, and economic systems to study emergent phenomena. Critics note a learning curve and the need for careful calibration, while proponents highlight modularity, extensibility, and strong documentation. The project maintains an active website and community forums for tutorials, examples, and contributions.