Abstract
An incremental learning algorithm for a special class of self-organising, dynamic networks is presented. Learning is effected by adapting both the function performed by the nodes and the overall network topology, so that the network grows (or shrinks) over time to fit the problem. Convergence is guaranteed on any arbitrary Boolean dataset and empirical generalisation results demonstrate promise.
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© 1995 Springer-Verlag/Wien
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Giraud-Carrier, C., Martinez, T. (1995). AA1*: A Dynamic Incremental Network that Learns by Discrimination. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_14
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DOI: https://doi.org/10.1007/978-3-7091-7535-4_14
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82692-8
Online ISBN: 978-3-7091-7535-4
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