GENITOR II.: a distributed genetic algorithm

This paper is the second part of a two-part paper which introduces a general schema theory for genetic programming (GP) with subtree-swapping crossover (Part I (Poli and McPhee, 2003)). Like other recent GP schema theory results, the theory gives an ...

Neural networks are a common and powerful tool to approximate highly complex non-linear functions. Most typically, the connection weights of these structures are adapted during training by employing gradient descent techniques. As this is not possible ...

ExGA I, a previously presented genetic algorithm, successfully solved numerous instances of the multiple knapsack problem (MKS) by employing an adaptive repair function that made use of the algorithm's modular encoding. Here we present ExGA II, an ...