Imprecise selection and fitness approximation in a large-scale evolutionary rule based system for blood pressure prediction

Authors:
Erik Hemberg;Kalyan Veeramachaneni;Franck Dernoncourt;Mark Wagy;Una-May O'Reilly
Affiliations:
MIT CSAIL, Cambridge, MA, USA;MIT CSAIL, Cambridge, MA, USA;MIT CSAIL, Cambridge, MA, USA;University of Vermont, Burlington, VT, USA;MIT CSAIL, Cambridge, MA, USA
Venue:
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Year:
2013

Citing 2
Cited 0

ALPS: the age-layered population structure for reducing the problem of premature convergence

Proceedings of the 8th annual conference on Genetic and evolutionary computation
Learning classifier systems: a complete introduction, review, and roadmap

Journal of Artificial Evolution and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present how we have strategically allocated fitness evaluations in a large-scale rule based evolutionary system called ECStar. We describe a strategy that culls potentially weaker solutions early, then later only compete with solutions which have equivalent fitness evaluations, as they are evaluated on more fitness cases. Despite incurring some imprecision in fitness comparison, which arises from not evaluating on all the fitness cases or even the same ones, the strategy allows our system to make effective progress when the resources at its disposal are unpredictably available.