Cognitive Machine Learning: Prologue

Sources of inspiration is one thing we do not lack in machine learning. This is what, for me at least, makes machine learning research such a rewarding and exciting area to work in. We gain inspiration from our traditional neighbours in statistics, signal processing and control engineering, information theory and statistical physics. But our fortune continues, and we can take further inspiration from biological and evolutionary systems and, of importance to this series, the cognitive sciences of sociology, psychology and neuroscience. I previously explored important inspirations for machine learning offered by neuroscience and unpacked the role of prediction, sparsity, modularity and complementary learning in building learning systems.