In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
In this paper, we prove for the first time that the learning complexity of Rocchio’s algorithm is O(d+d2 (log d+log n)) over the discretized vector space {0, . . . , n − 1}d ,...
: We introduce a graph-theoretic generalization of classical Arrow-Debreu economics, in which an undirected graph specifies which consumers or economies are permitted to engage in...
This paper describes a novel data mining approach that employs evolutionary programming to discover knowledge represented in Bayesian networks. There are two different approaches ...
In this paper, we examine on-line learning problems in which the target concept is allowed to change over time. In each trial a master algorithm receives predictions from a large ...