In Incremental Learning will the model be updated automatically? I came across Incremental Learning algorithms paper, where incremental algorithms are compared. I have problem with general understanding. Will the model be updated /adapts itself automatically when new data comes in?

Does it know by itself that new  data has arrived and it learns?

In general, can anyone explain how training, testing, and model adaption is carried out with such incremental algorithms?
Incremental learning is analogous to online learning. It is based on the assumption that your model can receive a continuous stream of data from which it can keep learning indefinitely. Training is therefore based on Mini-Batch Gradient Descent optimization: you feed batches of data into the Network as soon an new data comes in.

Hope this helps, otherwise let me know.