Empirical Study of the Influences of Genetic Parameters in the Training of a Neural Network

  • P. Gomes
  • F. Pereira
  • A. Silva
Conference paper


This paper presents the empirical results achieved in the computer system ROBOTS. This program simulates a virtual world, where agents, called robots, interact with an environment. Each robot is controlled by a neural network. The evolution of the robot behaviour (which is determined by the variation of the weights in the neural network) is done using a genetic algorithm. We describe the conceptual model used in ROBOTS. We also show how the genetic parameters and the environment itself influence the robot’s adaptation to the environment.


Neural Network Genetic Algorithm Virtual World Genetic Parameter Neural Network Architecture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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    V. Porto, D. Fogel, and L. Fogel. Alternative neural network training methods. IEEE Expert, pages 16–22, June 1995.Google Scholar

Copyright information

© Springer-Verlag Wien 1998

Authors and Affiliations

  • P. Gomes
    • 1
  • F. Pereira
    • 1
  • A. Silva
    • 2
  1. 1.Instituto Superior, de Engenharia de CoimbraPortugal
  2. 2.Instituto de Sistemas, e RobóticaPortugal

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