Single-Task Continual Offline Reinforcement Learning

arXiv:2404.12639v1 Announce Type: new
Abstract: In this paper, we study the continual learning problem of single-task offline reinforcement learning. In the past, continual reinforcement learning usually only dealt with multitasking, that is, learning multiple related or unrelated tasks in a row, but once each learned task was learned, it was not relearned, but only used in subsequent processes. However, offline reinforcement learning tasks require the continuously learning of multiple different datasets for the same task. Existing algorithms will try their …

abstract arxiv continual cs.lg multiple multitasking offline paper reinforcement reinforcement learning study tasks type