Multimodal Sequence Learning with a Cortically-Inspired Model
Résumé
We present in this paper a cortically-inspired model that learns to exploit regularities of sequences of perceptions and actions, with regard to motivations. Sequences are learned from continuous multimodal information streams, on the basis of a competition mechanism. This approach enables generalisations from perceptive regularities and also ensures the capability to apply results of previous learning to help further learning of new tasks.