GSGP-C++ 2.0: A geometric semantic genetic programming framework

2siGeometric semantic operators (GSOs) for Genetic Programming have been widely investigated in recent years, producing competitive results with respect to standard syntax based operator as well as other well-known machine learning techniques. The usage of GSOs has been facilitated by a C++ framework that implements these operators in a very efficient manner. This work presents a description of the system and focuses on a recently implemented feature that allows the user to store the information related to the best individual and to evaluate new data in a time that is linear with respect to the number of generations used to find the optimal individual. The paper presents the main features of the system and provides a step by step guide for interested users or developers.openopenCastelli Mauro; Manzoni LucaCastelli, Mauro; Manzoni, Luc