Genetic Programming offers freedom in the definition of the cost function that is unparalleled among supervised learning algorithms. However, this freedom goes largely unexploited...
Background. Currently there are several definitions of measures that should represent the size of software functional requirements. These measures have gained a quite relevant rol...
Background: The ability to design thermostable proteins is theoretically important and practically useful. Robust and accurate algorithms, however, remain elusive. One critical pr...
We introduce the first algorithm for off-policy temporal-difference learning that is stable with linear function approximation. Off-policy learning is of interest because it forms...
This paper describes an extension to the Restricted Growth Function grouping Genetic Algorithm applied to the Consensus Clustering of a retinal nerve fibre layer data-set. Consens...
Stephen Swift, Allan Tucker, Jason Crampton, David...