Continual learning – Definition & Meaning

Definition of continual learning

: an approach in which a machine-learning system learns from a sequence or stream of changing tasks and data while trying to retain useful knowledge from earlier learning
- Continual learning allowed the fraud model to adapt to new attack patterns without discarding everything learned last year.
- The robot used a replay buffer to balance continual learning with retention of earlier skills.

Origin & history

Continual learning grew from research on lifelong machine learning, adaptive systems, and catastrophic interference. The name became a standard research label in the late 2010s as benchmarks began evaluating models on sequential tasks and non-stationary data streams.

Test yourself

Which of these is the meaning of continual learning?

Related terms

catastrophic forgetting the abrupt loss of previously learned abilities or knowledge when a neural network is trained… concept drift a change over time in the statistical relationship between a model's inputs and the outcome it… fine-tuning further training of an existing model on a smaller, focused dataset so it gets better at a… post-training everything done to a model after pre-training to make it useful and safe, such as instruction… self-distillation a form of knowledge distillation in which a model learns from outputs, representations… test-time adaptation a family of methods that adjust a trained model, its internal statistics, or its predictions…

Cite this entry

"Continual learning." AI Dictionary, Dadgogo, https://dadgogo.com/dictionary/continual-learning/. Accessed 8 Oct. 2026.