Particle swarm optimization is a computational method inspired by the social behavior of birds and fish that finds optimal solutions by having a group of potential solutions, called particles, explore the search space. Each particle adjusts its position based on its own experience and the experiences of neighboring particles, leading to emergent behavior that allows for efficient optimization in complex problem spaces.
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