Fractional Genetic Programming for a More Gradual Evolution.
Artur Rataj · 2013
Abstract. We propose a softening of a genetic program by the so–called fractional instructions. Thanks to their adjustable strengths, a new instruction can be gradually introduced to a program, and the other instructions may gradually adapt to the new member. In this way, a transformation of one candidate into another can be continuous. Such an approach makes it possible to take advantage of properties of real–coded genetic algorithms, but in the realm of genetic programming. We show, that the approach can be successfully applied to a precise generalisation of functions, including those exhibiting periodicity.