Personally, I don’t expect much from the data. From reading through scores of papers comparing minute differences in spacing and getting contradictory results and small improvements, I get the impression that once you’ve moved from massed to spacing (almost any kind of spacing), you’ve gotten the overwhelming majority of the benefits, and the rest is basically frippery which needs a lot of domain expertise to improve upon. I understand Peter hasn’t looked at the Mnemosyne data much either because it didn’t indicate to him that the fancier SuperMemo algorithms were much help.
What do you think are the prospects of a SRS that uses a forgetting curve specific to the individual, by relying on past performance? Has this been tried or considered?
You can already modify the forgetting curve yourself in most SRS based on your needs via a constant. Unless an automatic algorithm goes with the personal best past performance, I expect a continuous decay of performance using such an algorithm for most individuals. I think Anki already automatically modifies intervals of individual cards based on your past performance i.e. the experienced difficulty and instances of forgetting, for example. New cards are not affected by past performance, as far as I know.
You need to specify which parts are being modified by an SRS system: each card has an easiness parameter and that will be continuously modified based your performance, but I don’t think existing SRS systems like Anki or Mnemosyne will modify other parts of the curve like the exponent. For example, SM2′s algorithm runs in part based on updating the easiness as EF+(0.1-(5-q)*(0.08+(5-q)*0.02)) - the EF will be progressively updated, but the formula itself never changes even if 0.1 is not ideal and 0.15 would be better or something.
What do you think are the prospects of a SRS that uses a forgetting curve specific to the individual, by relying on past performance? Has this been tried or considered?
You can already modify the forgetting curve yourself in most SRS based on your needs via a constant. Unless an automatic algorithm goes with the personal best past performance, I expect a continuous decay of performance using such an algorithm for most individuals. I think Anki already automatically modifies intervals of individual cards based on your past performance i.e. the experienced difficulty and instances of forgetting, for example. New cards are not affected by past performance, as far as I know.
You need to specify which parts are being modified by an SRS system: each card has an easiness parameter and that will be continuously modified based your performance, but I don’t think existing SRS systems like Anki or Mnemosyne will modify other parts of the curve like the exponent. For example, SM2′s algorithm runs in part based on updating the easiness as
EF+(0.1-(5-q)*(0.08+(5-q)*0.02))- the EF will be progressively updated, but the formula itself never changes even if 0.1 is not ideal and 0.15 would be better or something.