This paper introduces an approach called Clustering and Co-evolution to Construct Neural Network Ensembles (CONE). This approach creates neural network ensembles in an innovative ...
In concurrent cooperative multiagent learning, each agent simultaneously learns to improve the overall performance of the team, with no direct control over the actions chosen by i...
In this research, we compare four different evaluation methods in coevolution on the Majority Function problem. The size of the problem is selected such that an evaluation against...
— Many evolutionary algorithms have been proposed for large scale optimization. Parameter interaction in nonseparable problems is a major source of performance loss specially on ...
Abstract--We present an algorithm that coevolves fitness predictors, optimized for the solution population, which reduce fitness evaluation cost and frequency, while maintaining ev...