Particle Swarm Optimization
Version 1.0.0 · Updated 2026-07-30
CORE DEFINITION
Simulates the behavior of a flock of birds foraging. Each individual (particle) seeks the optimal solution based on its own experience while also referencing the group's optimal solution. Through the combination of 'individual cognition' and 'social cognition', the group can find the global optimum.
SCAFFOLDING EFFECT
Reduce cognitive load
Team balance. An ideal team is not one with only a single voice (everyone following the leader) nor a disorganized mess (each doing their own thing). Instead, each member explores independently while maintaining real-time awareness of teammates' positions.
Anchor fast decisions
Simulates birds foraging: each particle adjusts its velocity and position based on its own best and the group's best, and the group collaboratively converges to a good solution in the search space.
MINIMUM ACTION
In progress 0/4Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Particle_swarm_optimizationverified
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