Genetic programming evolves Lisp-like programs rather than fixed size linear strings. This representational power combined with generality makes genetic programming an interesting ...
A coevolutionary competitive learning environment for two antagonistic agents is presented. The agents are controlled by a new kind of computational network based on a compartment...
Gul Muhammad Khan, Julian Francis Miller, David M....
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...
Most association rule mining algorithms make use of discretization algorithms for handling continuous attributes. Discretization is a process of transforming a continuous attribute...
Karla Taboada, Eloy Gonzales, Kaoru Shimada, Shing...
Solving complex, real-world problems with genetic programming (GP) can require extensive computing resources. However, the highly parallel nature of GP facilitates using a large n...