Continual Learning of Multi-modal Dynamics with External Memory

arXiv:2203.00936v4 Announce Type: replace
Abstract: We study the problem of fitting a model to a dynamical environment when new modes of behavior emerge sequentially. The learning model is aware when a new mode appears, but it cannot access the true modes of individual training sequences. The state-of-the-art continual learning approaches cannot handle this setup, because parameter transfer suffers from catastrophic interference and episodic memory design requires the knowledge of the ground-truth modes of sequences. We devise a novel continual learning …

abstract access art arxiv behavior continual cs.lg dynamics environment memory modal multi-modal state stat.ml study training true type