Right now, there is only one implementation of this protocol, SSPop or steady state population. In this population model, all individuals in the population are ranked according to fitness, and a certain percentaje of them are eliminated. These are substituted by individuals resulting from the application of the unary and binary genetic operators available, with a certain rate, to the population. The percentage of population that is eliminated is equal to the sum of the rates of all operators. These rates can be altered during the execution of the GA, using set messages.
Fitness is always a floating point number, and is always maximized.
If you want to minimize it, just make the evaluation function return the inverse or the negative of the value.