An agent-based PLA for the cascade correlation learning architecture

Abstract

The paper proposes an implementation of the agent-based population learning algorithm (PLA) within the cascade correlation (CC) learning architecture. The first step of the CC procedure uses a standard learning algorithm. It is suggested that using the agent-based PLA as such an algorithm could improve efficiency of the approach. The paper gives a short overview of both - the CC algorithm and PLA, and then explains main features of the proposed agent-based PLA implementation. The approach is evaluated experimentally. © Springer-Verlag Berlin Heidelberg 2005.