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            my $pso = AI::ParticleSwarmOptimization::Pmap->new(
                -fitFunc    => [\&calcFit, $context],
                -dimensions => 3,
            );
        
            ...
        
            sub calcFit {
                my ($context, @values) = @_;
                ...
                return $fitness;
            }

	In addition to any user provided parameters the list of values
	representing the current particle position in the hyperspace is
	passed in. There is one value per hyperspace dimension.

      -inertia: positive or zero number, optional

	Determines what proportion of the previous velocity is carried
	forward to the next iteration. Defaults to 0.9

	See also -meWeight and -themWeight.

      -iterations: number, optional

	Number of optimization iterations to perform. Defaults to 1000.

      -meWeight: number, optional

	Coefficient determining the influence of the current local best
	position on the next iterations velocity. Defaults to 0.5.

	See also -inertia and -themWeight.

      -numNeighbors: positive number, optional

	Number of local particles considered to be part of the
	neighbourhood of the current particle. Defaults to the square root
	of the total number of particles.

      -numParticles: positive number, optional

	Number of particles in the swarm. Defaults to 10 times the number
	of dimensions.

      -posMax: number, optional

	Maximum coordinate value for any dimension in the hyper space.
	Defaults to 100.

      -posMin: number, optional

	Minimum coordinate value for any dimension in the hyper space.
	Defaults to --posMax (if -posMax is negative -posMin should be set
	more negative).

      -randSeed: number, optional

	Seed for the random number generator. Useful if you want to rerun
	an optimization, perhaps for benchmarking or test purposes.

      -randStartVelocity: boolean, optional

	Set true to initialize particles with a random velocity. Otherwise
	particle velocity is set to 0 on initalization.

	A range based on 1/100th of --posMax - -posMin is used for the
	initial speed in each dimension of the velocity vector if a random
	start velocity is used.

      -stallSpeed: positive number, optional

	Speed below which a particle is considered to be stalled and is
	repositioned to a new random location with a new initial speed.

	By default -stallSpeed is undefined but particles with a speed of 0
	will be repositioned.

      -themWeight: number, optional

	Coefficient determining the influence of the neighbourhod best
	position on the next iterations velocity. Defaults to 0.5.

	See also -inertia and -meWeight.

      -exitPlateau: boolean, optional

	Set true to have the optimization check for plateaus (regions where
	the fit hasn't improved much for a while) during the search. The
	optimization ends when a suitable plateau is detected following the
	burn in period.

	Defaults to undefined (option disabled).

      -exitPlateauDP: number, optional

	Specify the number of decimal places to compare between the current
	fitness function value and the mean of the previous
	-exitPlateauWindow values.

	Defaults to 10.

      -exitPlateauWindow: number, optional

	Specify the size of the window used to calculate the mean for
	comparison to the current output of the fitness function.
	Correlates to the minimum size of a plateau needed to end the
	optimization.

	Defaults to 10% of the number of iterations (-iterations).

      -exitPlateauBurnin: number, optional

	Determines how many iterations to run before checking for plateaus.

	Defaults to 50% of the number of iterations (-iterations).

      -verbose: flags, optional

	If set to a non-zero value -verbose determines the level of