Lifetime policy reuse and the importance of task capacity. (arXiv:2106.01741v2 [cs.LG] UPDATED)

A long-standing challenge in artificial intelligence is lifelong learning. In
lifelong learning, many tasks are presented in sequence and learners must
efficiently transfer knowledge between tasks while avoiding catastrophic
forgetting over long lifetimes. On these problems, policy reuse and other
multi-policy reinforcement learning techniques can learn many tasks. However,
they can generate many temporary or permanent policies, resulting in memory
issues. Consequently, there is a need for lifetime-scalable methods that
continually refine a policy library of a pre-defined size. This …

arxiv capacity importance policy