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General asymmetric neural networks and structure design by genetic algorithms

✍ Scribed by Stefan Bornholdt; Dirk Graudenz

Publisher: Elsevier Science
Year: 1992
Tongue: English
Weight: 666 KB
Volume: 5
Category: Article
ISSN: 0893-6080
DOI: 10.1016/s0893-6080(05)80030-9

No coin nor oath required. For personal study only.

✦ Synopsis

Abstraet--A learning algorithm for neural networks based on genetic algorithms is proposed. The concept leads in a natural way to a model for the explanation of inherited behavior. Explicitly we study a simplified model for a brain with sensory and motor neurons. We use a general asymmetric network whose structure is solely determined by an evolutionary process. This system is shnulated numerically. It turns out that the network obtained by the algorithm reaches a stable state after a small number of sweeps. Some results illustrating the learning capabilities are presented.

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