abstract = "There are two common methods of evolving teams of
genetic programs. Research suggests Island approaches
produce teams of strong individuals that cooperate
poorly and Team approaches produce teams of weak
individuals that cooperate strongly. Ideally, teams
should be composed of strong individuals that cooperate
well. In this paper we present a new class of
algorithms called Orthogonal Evolution of Teams (OET)
that overcomes the weaknesses of current Island and
Team approaches by applying evolutionary pressure at
both the level of teams and individuals during
selection and replacement. We present four novel
algorithms in this new class and compare their
performance to Island and Team approaches as well as
multi-class Adaboost on a number of classification
problems.",
notes = "GECCO-2007 A joint meeting of the sixteenth
international conference on genetic algorithms
(ICGA-2007) and the twelfth annual genetic programming
conference (GP-2007).