Artificial Neural Networks. Evolving Connectionist Systems

Abstract

Classical artificial neural networks (ANN) were developed to learn from data. Evolving connectionist systems (ECOS) were further developed by the author and taken further by other researchers not only to learn in an adaptive, incremental way from data that measure evolving processes, but to extract rules and knowledge from the trained systems. Both methods were initially inspired by some principles of learning in the brain, but then they were developed mainly as machine learning and AI tools and techniques, with a wider scope of applications. Many of the architectures and learning methods of ANN and ECOS were used in the development of SNN, deep learning systems and brain-inspired AI discussed in other chapters of the book.