The representation used by a learning algorithm introduces a bias which is more or less well-suited to any given learning problem. It is well known that, across all possible probl...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Many metaheuristics have difficulty exploring their search space comprehensively. Exploration time and efficiency are highly dependent on the size and the ruggedness of the search...
This research examines the behavior of inoperative code (introns) in the evolution of genetically robust solutions. Genetically robust solutions are solutions that are less likely...
We develop a new false-name-proof double auction protocol called the Generalized Threshold Price Double auction (GTPD) protocol. False-name-proofness generalizes strategyproofness...