[d110af5ccf]

The comment you replied to described an edge case and explained why it's broken in that particular case. You haven't actually responded to the example provided.

> it's just not clear if you're going to recall them or not. Figuring that out becomes the priority

Presumably the priority ought to be (re)starting with a small subset of cards and gradually trickling the others back in. The algorithm needs to account for time spent by the given individual and adapt to changes in that over time.

I haven't used Anki for about a decade so I'm not familiar with the current state of things. At the time a major factor in my dropping it was that I found the algorithm to be more of a hindrance than a help.

[zozbot234]

It's not at all clear that "restarting with a small subset of cards" is better. It means that you're very likely to fail to recall almost every card outside the small subset, which increases the work you must do to memorize the deck again. Any card that you verify immediately is going to save you a lot of work down the line.

[d110af5ccf]

> It's not at all clear that "restarting with a small subset of cards" is better.

Sure it is. It could grow as quickly as allowed for given the time invested by the user. That could mean a return to the full subset within the span of a single day, or it could mean many months. Perhaps even never. It all depends on time invested by the user going forward. Starving regular review for the sake of verification is an example of an algorithm failing when faced with the real world.

At minimum it is clear from what was said that (better) prioritization between conflicting goals is needed. That somewhat matches my own experience with it from years ago. The algorithm was simply not flexible enough to fit my own usage patterns. In other words I was not part of the target audience, which I found frustrating because I very easily could have been.