This software module enables users to run the Particle Swarm Optimization algorithm in order to solve optimization problems.
AI::PSO is a Perl module that offers the Particle Swarm Optimization algorithm. This algorithm is ideal for programmers seeking to optimize parameters. Specifically, you have the ability to optimize in four dimensions.
Like many software programs, AI::PSO provides a helpful synopsis for new users. With the use of this module, you'll be able to optimize your programs through certain key parameters. For example, you can set the number of particles involved in your search, as well as the number of neighbors an individual particle will share its progress with. Additionally, you can set a maximum number of iterations before you exit with no solution found.
But that's not all. In order to customize the AI program even more to your liking, you can set minimum and maximum random weight for both the "individuality" and "social" weighting constants. For instance, the higher the "social" constant weight value, the more it trusts the group.
To further customize your program, AI::PSO also offers you the ability to set your own custom fitness function. By setting this callback function, you will have the opportunity to provide an array of floats, and a value in [0,1] within.
When you're ready to optimize, simply input the parameters you've set in with pso_set_params(\%params) function. You can then optimize with pso_optimize(), and if you need to further optimize, retrieve the solution array with pso_get_solution_array().
Overall, AI::PSO is a user-friendly module with a variety of features that give you ultimate control over your program's optimization.
Like many software programs, AI::PSO provides a helpful synopsis for new users. With the use of this module, you'll be able to optimize your programs through certain key parameters. For example, you can set the number of particles involved in your search, as well as the number of neighbors an individual particle will share its progress with. Additionally, you can set a maximum number of iterations before you exit with no solution found.
But that's not all. In order to customize the AI program even more to your liking, you can set minimum and maximum random weight for both the "individuality" and "social" weighting constants. For instance, the higher the "social" constant weight value, the more it trusts the group.
To further customize your program, AI::PSO also offers you the ability to set your own custom fitness function. By setting this callback function, you will have the opportunity to provide an array of floats, and a value in [0,1] within.
When you're ready to optimize, simply input the parameters you've set in with pso_set_params(\%params) function. You can then optimize with pso_optimize(), and if you need to further optimize, retrieve the solution array with pso_get_solution_array().
Overall, AI::PSO is a user-friendly module with a variety of features that give you ultimate control over your program's optimization.
What's New
Version 0.86: N/A