Abstract
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.
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© 1998 Springer-Verlag Wien
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Gomes, P., Pereira, F., Silva, A. (1998). Empirical Study of the Influences of Genetic Parameters in the Training of a Neural Network. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6492-1_80
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DOI: https://doi.org/10.1007/978-3-7091-6492-1_80
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83087-1
Online ISBN: 978-3-7091-6492-1
eBook Packages: Springer Book Archive