In this paper, the authors compare a Monte Carlo method and an optimization-based approach using genetic algorithms for sequentially generating space-filling experimental designs....
This work addresses the problem of finding the adjustable parameters of a learning algorithm using Genetic Algorithms. This problem is also known as the model selection problem. In...
: This paper describes the successful parallel implementation of genetic programming on a network of processing nodes using the transputer architecture. With this approach, researc...