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Marco S. Nobile edited this page Oct 15, 2017 · 29 revisions

Welcome to the fst-pso wiki!

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What is FST-PSO?

FST-PSO is a settings-free version of the global optimization algorithm known as Particle Swarm Optimization. FST-PSO does not need any user settings to work, because particles leverage fuzzy logic to adapt their behavior to the fitness landscape.

Why FST-PSO?

FST-PSO was specifically design to be 1) extremely easy to use (no settings!) and 2) more effective than normal PSO. Thus, the API is extremely simple and straightforward:

  • create a FuzzyPSO class;
  • specify the search space with its set_search_space() method;
  • specify a fitness function with the set_fitness() method;
  • launch the optimization with the solve_with_fstpso() method.

Are there any optional settings?

Yes. You can pass the number of iterations as argument (max_iter) to solve_with_fstpso().

FST-PSO uses fuzzy logic to dynamically adapt the social factor, cognitive factor, inertia weight, maximum velocity, and minimum velocity of all particles

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