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arXiv · 2307.04345

Continual Learning as Computationally Constrained Reinforcement Learning

Saurabh Kumar·Henrik Marklund·Ashish Rao·Yifan Zhu·Hong Jun Jeon·Yueyang Liu·Benjamin Van Roy
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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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Saurabh Kumar, Henrik Marklund, Ashish Rao, Yifan Zhu, Hong Jun Jeon, Yueyang Liu, Benjamin Van Roy. 2023-07-10. Continual Learning as Computationally Constrained Reinforcement Learning. https://arxiv.org/abs/2307.04345

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