MODULAR NEURAL NETWORKS: A SURVEY

G. Auda, Mohamed S. Kamel

International Journal of Neural Systems · 1999 · 145 citations · 81 references

Concepts

TL;DR

Modular Neural Networks (MNNs) are a rapidly growing area within artificial neural network research. This survey examines the diverse motivations behind MNNs, including biological, psychological, hardware, and computational perspectives. The paper outlines the general stages of MNN design, covering task decomposition techniques, learning schemes, and multi‑module decision‑making strategies. The survey highlights the advantages and disadvantages of various MNN approaches, assesses their practical potential, and offers recommendations for future designs.

Abstract

Modular Neural Networks (MNNs) is a rapidly growing field in artificial Neural Networks (NNs) research. This paper surveys the different motivations for creating MNNs: biological, psychological, hardware, and computational. Then, the general stages of MNN design are outlined and surveyed as well, viz., task decomposition techniques, learning schemes and multi-module decision-making strategies. Advantages and disadvantages of the surveyed methods are pointed out, and an assessment with respect to practical potential is provided. Finally, some general recommendations for future designs are presented.

References

81