ImmuNetNAS: An Immune-network approach for searching Convolutional Neural Network Architectures

Understand

In this research, we propose ImmuNetNAS, a novel Neural Architecture Search (NAS) approach inspired by the immune network theory.

• The core of ImmuNetNAS is built on the original immune network algorithm, which iteratively updates the population through hypermutation and selection, and eliminates the self-generation individuals that do not meet the requirements through comparing antibody affinity and inter-specific similarity.
• In addition, in order to facilitate the mutation operation, we propose a novel two-component based neural structure coding strategy.
• Furthermore, an improved mutation strategy based on Standard Genetic Algorithm (SGA) was proposed according to this encoding method.