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The Algorithm
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$R$ : Retrievability (probability of recall) -
$S$ : Stability (interval when R=90%)-
$S^\prime_r$ : new stability after recall -
$S^\prime_f$ : new stability after forgetting
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$D$ : Difficulty ($D \in [1, 10]$ ) -
$G$ : Grade (rating at Anki):-
$1$ :again
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$2$ :hard
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$3$ :good
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$4$ :easy
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[1, 2, 3, 4, 5, 0.5, 0.5, 0.2, 1.4, 0.2, 0.8, 2, 0.2, 0.2, 1, 0.5, 2]
The
$w_i$ denotes w[i].
The initial stability after the first rating:
For example, again
. When the first rating is easy
, the initial stability is
The initial difficulty after the first rating:
where the good
.
The new difficulty after review:
It will calculate the new difficulty with
The retrievability after
where
The next interval can be calculated by solving for t in the above equation after putting the request retention in place of R:
where
The new stability after a successful review (the user pressed "Hard", "Good" or "Easy"):
Let
- The larger the value of D, the smaller the
$SInc$ , which means that for difficult material, the increase in memory stability is smaller than for easy material. - The larger the value of S, the smaller the
$SInc$ , which means that memory saturates. The more stable your memory is, the harder it is to make it even more stable. - The smaller the value of R, the larger the
$SInc$ , which means that the best time to review your material is when you almost forgot it. - The value of
$SInc$ is always greater than or equal to 1 if the review was successful.
The stability after forgetting (i.e., post-lapse stability):
For example, if
var w = [1, 1, 5, -1, -1, 0.1, 1.5, -0.2, 0.8, 2, -0.2, 0.2, 1];
The
$w_i$ denotes w[i].
The initial stability after the first rating:
where the again
. When the first rating is easy
, the initial stability is
The initial difficulty after the first rating:
where the good
.
The new difficulty after review:
It will calculate the new difficulty with
The retrievability of
where
The function of interval is the reverse function of retrievability:
where
The new stability after recall:
Let factor
.
- The larger the value of D, the smaller the
$SInc$ , which means that for difficult material, the increase in memory stability is smaller than for easy material. - The larger the value of S, the smaller the
$SInc$ , which means that memory saturates. The more stable your memory is, the harder it is to make it even more stable. - The smaller the value of R, the larger the
$SInc$ , which means that the best time to review your material is when you almost forgot it. - The value of
$SInc$ is always greater than or equal to 1 if the review was successful.
The following 3D visualization could help understand.
The stability after forgetting (i.e., post-lapse stability):
For example, if
You can play the function in post-lapse stability - GeoGebra.
My representative paper at ACMKDD: A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling
My fantastic research experience on spaced repetition algorithm: How did I publish a paper in ACMKDD as an undergraduate?
The largest open-source dataset on spaced repetition with time-series features: open-spaced-repetition/FSRS-Anki-20k