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Recording individual agent metrics and global variables at every time step for post-simulation analysis.
Distinct from Data Collection Architectures: Specifically records the state of a simulation over time, unlike system monitoring agents or general statistics tools.
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Mesa is a Python framework for agent-based modeling and complex systems simulation. It provides a toolkit for creating simulations where autonomous agents interact within a shared environment to observe emergent global behaviors. The project includes a browser-based interface for real-time visualization of simulation states and agent interactions. It also functions as a data analysis library for recording and processing metrics from model runs to quantify system behavior. The framework supports multiple environmental topologies, including grid-based spatial mapping and network-graph topologi
Records agent metrics and global system variables at every time step for statistical analysis.