However, having the prediction error statistic can be useful in its own right. For example, in recent experiments on the explore/exploit tradeoff, I've used the error (meaning the moving average) for decisions as to whether a given action has been sufficiently tried. A large error may mean the prediction is not well established, and more exploration of that action should occur.
The only place the prediction error parameter is used is in the fitness update calculation. Why not simply use the absolute difference between P and p sub j in the fitness update?