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Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005

Volume 3697 of the series Lecture Notes in Computer Science pp 197-202

An Agent-Based PLA for the Cascade Correlation Learning Architecture

  • Ireneusz CzarnowskiAffiliated withDepartment of Information Systems, Gdynia Maritime University
  • , Piotr JędrzejowiczAffiliated withDepartment of Information Systems, Gdynia Maritime University

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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.