Continual Learning as Computationally Constrained Reinforcement Learning

Saurabh Kumar, Henrik Marklund, Ashish Rao, Yifan Zhu, Hong Jun Jeon +2 more
7/10/2023
cs.LGcs.AI

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Abstract

An agent that efficiently accumulates knowledge to develop increasingly sophisticated skills over a long lifetime could advance the frontier of artificial intelligence capabilities. The design of such agents, which remains a long-standing challenge of artificial intelligence, is addressed by the subject of continual learning. This monograph clarifies and formalizes concepts of continual learning, introducing a framework and set of tools to stimulate further research.

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Cite this paper

@article{kumar2023continual,
  title  = {Continual Learning as Computationally Constrained Reinforcement Learning},
  author = {Saurabh Kumar and Henrik Marklund and Ashish Rao and Yifan Zhu and Hong Jun Jeon and Yueyang Liu and Benjamin Van Roy},
  year   = {2023},
  eprint = {2307.04345},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2307.04345v3}
}

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