Continual Learning as Computationally Constrained Reinforcement Learning

• URL: http://arxiv.org/abs/2307.04345v2
• Date: Sun, 20 Aug 2023 19:58:49 GMT
• Title: Continual Learning as Computationally Constrained Reinforcement Learning
• Authors: Saurabh Kumar, Henrik Marklund, Ashish Rao, Yifan Zhu, Hong Jun Jeon, Yueyang Liu, and Benjamin Van Roy
• Abstract summary: 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.
• Score: 23.88768480916785
• License: http://creativecommons.org/licenses/by/4.0/
• 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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