METRA: Scalable Unsupervised RL with Metric-Aware Abstraction

arXiv:2310.08887v2 Announce Type: replace
Abstract: Unsupervised pre-training strategies have proven to be highly effective in natural language processing and computer vision. Likewise, unsupervised reinforcement learning (RL) holds the promise of discovering a variety of potentially useful behaviors that can accelerate the learning of a wide array of downstream tasks. Previous unsupervised RL approaches have mainly focused on pure exploration and mutual information skill learning. However, despite the previous attempts, making unsupervised RL truly scalable still remains a major open challenge: …

abstraction arxiv cs.ai cs.lg cs.ro scalable type unsupervised