s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
Abstract-- We investigate the usefulness of a subtree deactivation control mechanism which is open to evolutionary learning. It is hypothesised that this representation confers an ...
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
The application of Inductive Logic Programming to scientific datasets has been highly successful. Such applications have led to breakthroughs in the domain of interest and have dri...
Bid-based Genetic Programming (GP) provides an elegant mechanism for facilitating cooperative problem decomposition without an a priori specification of the number of team member...