Particle Swarm Optimization (PSO)
Particle Swarm Optimization (PSO) is a swarm intelligence method for numerical optimization. Here, the candidate solutions are represented by particles flying through ${\mathbb{R}}^n$, each having a velocity vector. The velocities of the particles are influenced by neighboring particles and by the objective function via best-so-far positions.
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Why research in Computational Intelligence should be less nature-inspired.
The inspiration gleaned from observing nature has led to several important advances in the field of optimization. Still, it seems to me that a lot of work is mainly based on such inspiration alone. This might divert attention away from practical and algorithmic concerns. As a result, there is a growing number of specialized terminologies used in the field of Evolutionary Computation (EC) and Swarm Intelligence (SI), which I consider as a problem for clarity in research. With this article, I would like to formulate my thoughts with the hope to contribute to a fruitful debate.