meta-learning-three-formal-requirements
IN premise — summaries/2026/08/24/wiki-Meta-learning_computer_science.md
Created 2026-08-25T02:58:50+00:00
A meta-learning system must (1) include a learning subsystem, (2) gain experience from meta-knowledge extracted in previous episodes or across domains, and (3) choose its learning bias dynamically.
Summary
This sets the minimum bar for calling something a meta-learning system: it has to actually learn, carry forward lessons from past episodes or other contexts, and adjust its learning strategy on the fly rather than locking into one fixed approach. Anything missing one of those three components is just ordinary learning or a rigid pipeline, not true meta-learning.