Affective Manifold

Affective manifolds represent a novel approach to modeling emotions in machines, aiming to create more human-like and nuanced emotional responses in artificial intelligence. Current research focuses on developing methods to learn and manipulate these manifolds, often employing deep metric learning techniques like Siamese networks and exploring the disentanglement of emotional intensities within a manifold's structure. This work has implications for improving human-computer interaction and creating more sophisticated and believable AI agents capable of expressing a wider range of emotions.