Boids is a rule-based agent simulation model introduced by Craig Reynolds that governs the emergent collective movement of individual agents through three core behavioral rules: separation (avoiding crowding neighbors), alignment (steering toward the average heading of neighbors), and cohesion (moving toward the average position of neighbors). In the context of crowd simulation and sensing research, Boids matters because it provides a computationally tractable and biologically inspired framework for replicating realistic group locomotion patterns, which underpins the design and evaluation of more complex crowd models used in WiFi/CSI-based occupancy and motion sensing. Key variants extend the original three-rule formulation by incorporating additional parameters such as obstacle avoidance, goal-directed navigation, and heterogeneous agent behaviors, allowing the model to be tuned and benchmarked against real pedestrian trajectory data as part of parameter optimization frameworks for crowd simulation evaluation.
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