Audit Protocol for Continual Learning Agents
This paper discusses the challenges of auditing continual learning agents, which are designed to learn continuously over time. The authors highlight a key issue where traditional methods can reject useful updates while still allowing harmful ones. They propose new criteria and metrics to address this problem, including a paired-binomial construction for better error control and retained learning…
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Key points
- Authors propose new criteria for auditing continual learning agents
- Paired-binomial construction improves error control and retained learning opportunities
- Simulation results show significant improvement in update admission rates
Read the original at arXiv cs.AI · by Qinzhen Ma, Ruihai Wu primary source Open source ↗
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